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Archive for the ‘Data Science’ Category

Revolutionizing Business with Apple Vision Pro: The Ultimate Tool for Enhanced Visual Communication

Reporter: Frason Francis Kalapurackal, BE

Image Source: https://www.trustedreviews.com/versus/apple-vision-pro-vs-meta-quest-3-4333959

In today’s fast-paced business world, effective visual communication is more important than ever. This is where Apple Vision Pro comes in, serving as the ultimate tool for enhancing visual communication in the workplace. With its innovative software solution, it revolutionizes the way businesses communicate by providing new and improved methods for creating, editing, and sharing visual content. Apple Vision Pro boasts a user-friendly interface and advanced features that have made it an indispensable asset for businesses seeking to streamline their visual communication processes and boost productivity. The software empowers businesses to generate professional-looking visuals that are easily shareable and foster collaboration, making it an invaluable tool for staying ahead in today’s competitive landscape.

Apple Vision Pro sets itself apart with cutting-edge features such as augmented reality and machine learning, enabling users to create immersive and informative content. Through this tool, businesses can effortlessly produce and distribute videos, presentations, and other visual materials, making it a must-have for business owners, marketers, and creative professionals alike.

The impact of Apple Vision Pro is transformative, revolutionizing how businesses communicate visually. With its advanced capabilities and intuitive interface, it empowers users to craft visually stunning content that not only captivates but also educates. The tool offers a diverse range of visual elements like charts, graphs, images, and videos, enabling the effective conveyance of complex information to audiences. Furthermore, Apple Vision Pro facilitates real-time collaboration, making it easier for teams to work together, generate content collectively, and share ideas seamlessly. These capabilities enable businesses to enhance their visual communication efforts and create more impactful content, ultimately driving them towards achieving their goals with greater efficiency and effectiveness.

Some of the potential applications of Apple Vision Pro:

  1. Gaming: Vision Pro could be used for gaming by providing a more immersive experience.
  2. Productivity: Vision Pro could be used for productivity applications by providing a more natural way to interact with computers.
  3. Creative applications: Vision Pro could be used for creative applications by providing a more immersive way to create and edit content.
  4. Education: Vision Pro could be used for education by providing a more immersive way to learn.
  5. Training: Vision Pro could be used for training by providing a more immersive way to learn new skills.
  6. Remote collaboration: Vision Pro could be used for remote collaboration by providing a more immersive way to work with others.

Source Link:

https://www.forbes.com/sites/traceyfollows/2023/06/15/apple-vision-pro-signals-another-move-into-digital-identity-for-apple/?sh=36a7cf9b63d8

https://hbr.org/2023/06/what-is-apples-vision-pro-really-for

https://www.zdnet.com/article/apples-vision-pro-a-concept-prototype-with-this-enormous-potential/

https://www.core77.com/posts/123826/What-are-the-Actual-Applications-for-Apples-Vision-Pro-Goggles

Other related articles published in this Open Access Online Scientific Journal include the following:

3 articles in the Category:

‘Wearable Tech + Digital Health’ 

https://pharmaceuticalintelligence.com/category/wearable-tech-digital-health/

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Reporter: Frason Francis Kalapurakal, Research Assistant II

Researchers from MIT and Technion have made a significant contribution to the field of machine learning by developing an adaptive algorithm that addresses the challenge of determining when a machine should follow a teacher’s instructions or explore on its own. The algorithm autonomously decides whether to use imitation learning, which involves mimicking the behavior of a skilled teacher, or reinforcement learning, which relies on trial and error to learn from the environment.

The researchers’ key innovation lies in the algorithm’s adaptability and ability to determine the most effective learning method throughout the training process. To achieve this, they trained two “students” with different learning approaches: one using a combination of reinforcement and imitation learning, and the other relying solely on reinforcement learning. The algorithm continuously compared the performance of these two students, adjusting the emphasis on imitation or reinforcement learning based on which student achieved better results.

The algorithm’s efficacy was tested through simulated training scenarios, such as navigating mazes or reorienting objects with touch sensors. In all cases, the algorithm demonstrated superior performance compared to non-adaptive methods, achieving nearly perfect success rates and significantly outperforming other methods in terms of both accuracy and speed. This adaptability could enhance the training of machines in real-world situations where uncertainty is prevalent, such as robots navigating unfamiliar buildings or performing complex tasks involving object manipulation and locomotion.

Furthermore, the algorithm’s potential applications extend beyond robotics to various domains where imitation or reinforcement learning is employed. For example, large language models like GPT-4 could be used as teachers to train smaller models to excel in specific tasks. The researchers also suggest that analyzing the similarities and differences between machines and humans learning from their respective teachers could provide valuable insights for improving the learning experience.The MIT and Technion researchers’ algorithm stands out due to its principled approach, efficiency, and versatility across different domains. Unlike existing methods that require brute-force trial-and-error or manual tuning of parameters, their algorithm dynamically adjusts the balance between imitation and trial-and-error learning based on performance comparisons. This robustness, adaptability, and promising results make it a noteworthy advancement in the field of machine learning.

References:

“TGRL: TEACHER GUIDED REINFORCEMENT LEARNING ALGORITHM FOR POMDPS” Reincarnating Reinforcement Learning Workshop at ICLR 2023 https://openreview.net/pdf?id=kTqjkIvjj7

https://arxiv.org/abs/2301.01219

Reinforcement Learning: A Survey by L. P. Kaelbling, M. L. Littman, A. W. Moore https://doi.org/10.48550/arXiv.cs/9605103

Concrete Problems in AI Safety by Dario Amodei, Chris Olah, Jacob Steinhardt, Paul Christiano, John Schulman, Dan Mané https://arxiv.org/abs/1606.06565

Other related articles published in this Open Access Online Scientific Journal include the following:

92 articles in the Category:

‘Artificial Intelligence – Breakthroughs in Theories and Technologies’ 

https://pharmaceuticalintelligence.com/category/artificial-intelligence-general/artificial-intelligence-breakthroughs-in-theories-and-technologies/

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Developing Machine Learning Models for Prediction of Onset of Type-2 Diabetes

Reporter: Amandeep Kaur, B.Sc., M.Sc.

A recent study reports the development of an advanced AI algorithm which predicts up to five years in advance the starting of type 2 diabetes by utilizing regularly collected medical data. Researchers described their AI model as notable and distinctive based on the specific design which perform assessments at the population level.

The first author Mathieu Ravaut, M.Sc. of the University of Toronto and other team members stated that “The main purpose of our model was to inform population health planning and management for the prevention of diabetes that incorporates health equity. It was not our goal for this model to be applied in the context of individual patient care.”

Research group collected data from 2006 to 2016 of approximately 2.1 million patients treated at the same healthcare system in Ontario, Canada. Even though the patients were belonged to the same area, the authors highlighted that Ontario encompasses a diverse and large population.

The newly developed algorithm was instructed with data of approximately 1.6 million patients, validated with data of about 243,000 patients and evaluated with more than 236,000 patient’s data. The data used to improve the algorithm included the medical history of each patient from previous two years- prescriptions, medications, lab tests and demographic information.

When predicting the onset of type 2 diabetes within five years, the algorithm model reached a test area under the ROC curve of 80.26.

The authors reported that “Our model showed consistent calibration across sex, immigration status, racial/ethnic and material deprivation, and a low to moderate number of events in the health care history of the patient. The cohort was representative of the whole population of Ontario, which is itself among the most diverse in the world. The model was well calibrated, and its discrimination, although with a slightly different end goal, was competitive with results reported in the literature for other machine learning–based studies that used more granular clinical data from electronic medical records without any modifications to the original test set distribution.”

This model could potentially improve the healthcare system of countries equipped with thorough administrative databases and aim towards specific cohorts that may encounter the faulty outcomes.

Research group stated that “Because our machine learning model included social determinants of health that are known to contribute to diabetes risk, our population-wide approach to risk assessment may represent a tool for addressing health disparities.”

Sources:

https://www.cardiovascularbusiness.com/topics/prevention-risk-reduction/new-ai-model-healthcare-data-predict-type-2-diabetes?utm_source=newsletter

Reference:

Ravaut M, Harish V, Sadeghi H, et al. Development and Validation of a Machine Learning Model Using Administrative Health Data to Predict Onset of Type 2 Diabetes. JAMA Netw Open. 2021;4(5):e2111315. doi:10.1001/jamanetworkopen.2021.11315 https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2780137

Other related articles were published in this Open Access Online Scientific Journal, including the following:

AI in Drug Discovery: Data Science and Core Biology @Merck &Co, Inc., @GNS Healthcare, @QuartzBio, @Benevolent AI and Nuritas

Reporters: Aviva Lev-Ari, PhD, RN and Irina Robu, PhD

https://pharmaceuticalintelligence.com/2020/08/27/ai-in-drug-discovery-data-science-and-core-biology-merck-co-inc-gns-healthcare-quartzbio-benevolent-ai-and-nuritas/

Can Blockchain Technology and Artificial Intelligence Cure What Ails Biomedical Research and Healthcare

Curator: Stephen J. Williams, Ph.D.

https://pharmaceuticalintelligence.com/2018/12/10/can-blockchain-technology-and-artificial-intelligence-cure-what-ails-biomedical-research-and-healthcare/

HealthCare focused AI Startups from the 100 Companies Leading the Way in A.I. Globally

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2018/01/18/healthcare-focused-ai-startups-from-the-100-companies-leading-the-way-in-a-i-globally/

AI in Psychiatric Treatment – Using Machine Learning to Increase Treatment Efficacy in Mental Health

Reporter: Aviva Lev- Ari, PhD, RN

https://pharmaceuticalintelligence.com/2019/06/04/ai-in-psychiatric-treatment-using-machine-learning-to-increase-treatment-efficacy-in-mental-health/

Vyasa Analytics Demos Deep Learning Software for Life Sciences at Bio-IT World 2018 – Vyasa’s booth (#632)

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2018/05/10/vyasa-analytics-demos-deep-learning-software-for-life-sciences-at-bio-it-world-2018-vyasas-booth-632/

New Diabetes Treatment Using Smart Artificial Beta Cells

Reporter: Irina Robu, PhD

https://pharmaceuticalintelligence.com/2017/11/08/new-diabetes-treatment-using-smart-artificial-beta-cells/

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Live Notes, Real Time Conference Coverage AACR 2020 #AACR20: Tuesday June 23, 2020 Noon-2:45 Educational Sessions

Live Notes, Real Time Conference Coverage AACR 2020: Tuesday June 23, 2020 Noon-2:45 Educational Sessions

Reporter: Stephen J. Williams, PhD

Follow Live in Real Time using

#AACR20

@pharma_BI

@AACR

Register for FREE at https://www.aacr.org/

 

Presidential Address

Elaine R Mardis, William N Hait

DETAILS

Welcome and introduction

William N Hait

 

Improving diagnostic yield in pediatric cancer precision medicine

Elaine R Mardis
  • Advent of genomics have revolutionized how we diagnose and treat lung cancer
  • We are currently needing to understand the driver mutations and variants where we can personalize therapy
  • PD-L1 and other checkpoint therapy have not really been used in pediatric cancers even though CAR-T have been successful
  • The incidence rates and mortality rates of pediatric cancers are rising
  • Large scale study of over 700 pediatric cancers show cancers driven by epigenetic drivers or fusion proteins. Need for transcriptomics.  Also study demonstrated that we have underestimated germ line mutations and hereditary factors.
  • They put together a database to nominate patients on their IGM Cancer protocol. Involves genetic counseling and obtaining germ line samples to determine hereditary factors.  RNA and protein are evaluated as well as exome sequencing. RNASeq and Archer Dx test to identify driver fusions
  • PECAN curated database from St. Jude used to determine driver mutations. They use multiple databases and overlap within these databases and knowledge base to determine or weed out false positives
  • They have used these studies to understand the immune infiltrate into recurrent cancers (CytoCure)
  • They found 40 germline cancer predisposition genes, 47 driver somatic fusion proteins, 81 potential actionable targets, 106 CNV, 196 meaningful somatic driver mutations

 

 

Tuesday, June 23

12:00 PM – 12:30 PM EDT

Awards and Lectures

NCI Director’s Address

Norman E Sharpless, Elaine R Mardis

DETAILS

Introduction: Elaine Mardis

 

NCI Director Address: Norman E Sharpless
  • They are functioning well at NCI with respect to grant reviews, research, and general functions in spite of the COVID pandemic and the massive demonstrations on also focusing on the disparities which occur in cancer research field and cancer care
  • There are ongoing efforts at NCI to make a positive difference in racial injustice, diversity in the cancer workforce, and for patients as well
  • Need a diverse workforce across the cancer research and care spectrum
  • Data show that areas where the clinicians are successful in putting African Americans on clinical trials are areas (geographic and site specific) where health disparities are narrowing
  • Grants through NCI new SeroNet for COVID-19 serologic testing funded by two RFAs through NIAD (RFA-CA-30-038 and RFA-CA-20-039) and will close on July 22, 2020

 

Tuesday, June 23

12:45 PM – 1:46 PM EDT

Virtual Educational Session

Immunology, Tumor Biology, Experimental and Molecular Therapeutics, Molecular and Cellular Biology/Genetics

Tumor Immunology and Immunotherapy for Nonimmunologists: Innovation and Discovery in Immune-Oncology

This educational session will update cancer researchers and clinicians about the latest developments in the detailed understanding of the types and roles of immune cells in tumors. It will summarize current knowledge about the types of T cells, natural killer cells, B cells, and myeloid cells in tumors and discuss current knowledge about the roles these cells play in the antitumor immune response. The session will feature some of the most promising up-and-coming cancer immunologists who will inform about their latest strategies to harness the immune system to promote more effective therapies.

Judith A Varner, Yuliya Pylayeva-Gupta

 

Introduction

Judith A Varner
New techniques reveal critical roles of myeloid cells in tumor development and progression
  • Different type of cells are becoming targets for immune checkpoint like myeloid cells
  • In T cell excluded or desert tumors T cells are held at periphery so myeloid cells can infiltrate though so macrophages might be effective in these immune t cell naïve tumors, macrophages are most abundant types of immune cells in tumors
  • CXCLs are potential targets
  • PI3K delta inhibitors,
  • Reduce the infiltrate of myeloid tumor suppressor cells like macrophages
  • When should we give myeloid or T cell therapy is the issue
Judith A Varner
Novel strategies to harness T-cell biology for cancer therapy
Positive and negative roles of B cells in cancer
Yuliya Pylayeva-Gupta
New approaches in cancer immunotherapy: Programming bacteria to induce systemic antitumor immunity

 

 

Tuesday, June 23

12:45 PM – 1:46 PM EDT

Virtual Educational Session

Cancer Chemistry

Chemistry to the Clinic: Part 2: Irreversible Inhibitors as Potential Anticancer Agents

There are numerous examples of highly successful covalent drugs such as aspirin and penicillin that have been in use for a long period of time. Despite historical success, there was a period of reluctance among many to purse covalent drugs based on concerns about toxicity. With advances in understanding features of a well-designed covalent drug, new techniques to discover and characterize covalent inhibitors, and clinical success of new covalent cancer drugs in recent years, there is renewed interest in covalent compounds. This session will provide a broad look at covalent probe compounds and drug development, including a historical perspective, examination of warheads and electrophilic amino acids, the role of chemoproteomics, and case studies.

Benjamin F Cravatt, Richard A. Ward, Sara J Buhrlage

 

Discovering and optimizing covalent small-molecule ligands by chemical proteomics

Benjamin F Cravatt
  • Multiple approaches are being investigated to find new covalent inhibitors such as: 1) cysteine reactivity mapping, 2) mapping cysteine ligandability, 3) and functional screening in phenotypic assays for electrophilic compounds
  • Using fluorescent activity probes in proteomic screens; have broad useability in the proteome but can be specific
  • They screened quiescent versus stimulated T cells to determine reactive cysteines in a phenotypic screen and analyzed by MS proteomics (cysteine reactivity profiling); can quantitate 15000 to 20,000 reactive cysteines
  • Isocitrate dehydrogenase 1 and adapter protein LCP-1 are two examples of changes in reactive cysteines they have seen using this method
  • They use scout molecules to target ligands or proteins with reactive cysteines
  • For phenotypic screens they first use a cytotoxic assay to screen out toxic compounds which just kill cells without causing T cell activation (like IL10 secretion)
  • INTERESTINGLY coupling these MS reactive cysteine screens with phenotypic screens you can find NONCANONICAL mechanisms of many of these target proteins (many of the compounds found targets which were not predicted or known)

Electrophilic warheads and nucleophilic amino acids: A chemical and computational perspective on covalent modifier

The covalent targeting of cysteine residues in drug discovery and its application to the discovery of Osimertinib

Richard A. Ward
  • Cysteine activation: thiolate form of cysteine is a strong nucleophile
  • Thiolate form preferred in polar environment
  • Activation can be assisted by neighboring residues; pKA will have an effect on deprotonation
  • pKas of cysteine vary in EGFR
  • cysteine that are too reactive give toxicity while not reactive enough are ineffective

 

Accelerating drug discovery with lysine-targeted covalent probes

 

Tuesday, June 23

12:45 PM – 2:15 PM EDT

Virtual Educational Session

Molecular and Cellular Biology/Genetics

Virtual Educational Session

Tumor Biology, Immunology

Metabolism and Tumor Microenvironment

This Educational Session aims to guide discussion on the heterogeneous cells and metabolism in the tumor microenvironment. It is now clear that the diversity of cells in tumors each require distinct metabolic programs to survive and proliferate. Tumors, however, are genetically programmed for high rates of metabolism and can present a metabolically hostile environment in which nutrient competition and hypoxia can limit antitumor immunity.

Jeffrey C Rathmell, Lydia Lynch, Mara H Sherman, Greg M Delgoffe

 

T-cell metabolism and metabolic reprogramming antitumor immunity

Jeffrey C Rathmell

Introduction

Jeffrey C Rathmell

Metabolic functions of cancer-associated fibroblasts

Mara H Sherman

Tumor microenvironment metabolism and its effects on antitumor immunity and immunotherapeutic response

Greg M Delgoffe
  • Multiple metabolites, reactive oxygen species within the tumor microenvironment; is there heterogeneity within the TME metabolome which can predict their ability to be immunosensitive
  • Took melanoma cells and looked at metabolism using Seahorse (glycolysis): and there was vast heterogeneity in melanoma tumor cells; some just do oxphos and no glycolytic metabolism (inverse Warburg)
  • As they profiled whole tumors they could separate out the metabolism of each cell type within the tumor and could look at T cells versus stromal CAFs or tumor cells and characterized cells as indolent or metabolic
  • T cells from hyerglycolytic tumors were fine but from high glycolysis the T cells were more indolent
  • When knock down glucose transporter the cells become more glycolytic
  • If patient had high oxidative metabolism had low PDL1 sensitivity
  • Showed this result in head and neck cancer as well
  • Metformin a complex 1 inhibitor which is not as toxic as most mito oxphos inhibitors the T cells have less hypoxia and can remodel the TME and stimulate the immune response
  • Metformin now in clinical trials
  • T cells though seem metabolically restricted; T cells that infiltrate tumors are low mitochondrial phosph cells
  • T cells from tumors have defective mitochondria or little respiratory capacity
  • They have some preliminary findings that metabolic inhibitors may help with CAR-T therapy

Obesity, lipids and suppression of anti-tumor immunity

Lydia Lynch
  • Hypothesis: obesity causes issues with anti tumor immunity
  • Less NK cells in obese people; also produce less IFN gamma
  • RNASeq on NOD mice; granzymes and perforins at top of list of obese downregulated
  • Upregulated genes that were upregulated involved in lipid metabolism
  • All were PPAR target genes
  • NK cells from obese patients takes up palmitate and this reduces their glycolysis but OXPHOS also reduced; they think increased FFA basically overloads mitochondria
  • PPAR alpha gamma activation mimics obesity

 

 

Tuesday, June 23

12:45 PM – 2:45 PM EDT

Virtual Educational Session

Clinical Research Excluding Trials

The Evolving Role of the Pathologist in Cancer Research

Long recognized for their role in cancer diagnosis and prognostication, pathologists are beginning to leverage a variety of digital imaging technologies and computational tools to improve both clinical practice and cancer research. Remarkably, the emergence of artificial intelligence (AI) and machine learning algorithms for analyzing pathology specimens is poised to not only augment the resolution and accuracy of clinical diagnosis, but also fundamentally transform the role of the pathologist in cancer science and precision oncology. This session will discuss what pathologists are currently able to achieve with these new technologies, present their challenges and barriers, and overview their future possibilities in cancer diagnosis and research. The session will also include discussions of what is practical and doable in the clinic for diagnostic and clinical oncology in comparison to technologies and approaches primarily utilized to accelerate cancer research.

 

Jorge S Reis-Filho, Thomas J Fuchs, David L Rimm, Jayanta Debnath

DETAILS

Tuesday, June 23

12:45 PM – 2:45 PM EDT

 

High-dimensional imaging technologies in cancer research

David L Rimm

  • Using old methods and new methods; so cell counting you use to find the cells then phenotype; with quantification like with Aqua use densitometry of positive signal to determine a threshold to determine presence of a cell for counting
  • Hiplex versus multiplex imaging where you have ten channels to measure by cycling of flour on antibody (can get up to 20plex)
  • Hiplex can be coupled with Mass spectrometry (Imaging Mass spectrometry, based on heavy metal tags on mAbs)
  • However it will still take a trained pathologist to define regions of interest or field of desired view

 

Introduction

Jayanta Debnath

Challenges and barriers of implementing AI tools for cancer diagnostics

Jorge S Reis-Filho

Implementing robust digital pathology workflows into clinical practice and cancer research

Jayanta Debnath

Invited Speaker

Thomas J Fuchs
  • Founder of spinout of Memorial Sloan Kettering
  • Separates AI from computational algothimic
  • Dealing with not just machines but integrating human intelligence
  • Making decision for the patients must involve human decision making as well
  • How do we get experts to do these decisions faster
  • AI in pathology: what is difficult? =è sandbox scenarios where machines are great,; curated datasets; human decision support systems or maps; or try to predict nature
  • 1) learn rules made by humans; human to human scenario 2)constrained nature 3)unconstrained nature like images and or behavior 4) predict nature response to nature response to itself
  • In sandbox scenario the rules are set in stone and machines are great like chess playing
  • In second scenario can train computer to predict what a human would predict
  • So third scenario is like driving cars
  • System on constrained nature or constrained dataset will take a long time for commuter to get to decision
  • Fourth category is long term data collection project
  • He is finding it is still finding it is still is difficult to predict nature so going from clinical finding to prognosis still does not have good predictability with AI alone; need for human involvement
  • End to end partnering (EPL) is a new way where humans can get more involved with the algorithm and assist with the problem of constrained data
  • An example of a workflow for pathology would be as follows from Campanella et al 2019 Nature Medicine: obtain digital images (they digitized a million slides), train a massive data set with highthroughput computing (needed a lot of time and big software developing effort), and then train it using input be the best expert pathologists (nature to human and unconstrained because no data curation done)
  • Led to first clinically grade machine learning system (Camelyon16 was the challenge for detecting metastatic cells in lymph tissue; tested on 12,000 patients from 45 countries)
  • The first big hurdle was moving from manually annotated slides (which was a big bottleneck) to automatically extracted data from path reports).
  • Now problem is in prediction: How can we bridge the gap from predicting humans to predicting nature?
  • With an AI system pathologist drastically improved the ability to detect very small lesions

 

Virtual Educational Session

Epidemiology

Cancer Increases in Younger Populations: Where Are They Coming from?

Incidence rates of several cancers (e.g., colorectal, pancreatic, and breast cancers) are rising in younger populations, which contrasts with either declining or more slowly rising incidence in older populations. Early-onset cancers are also more aggressive and have different tumor characteristics than those in older populations. Evidence on risk factors and contributors to early-onset cancers is emerging. In this Educational Session, the trends and burden, potential causes, risk factors, and tumor characteristics of early-onset cancers will be covered. Presenters will focus on colorectal and breast cancer, which are among the most common causes of cancer deaths in younger people. Potential mechanisms of early-onset cancers and racial/ethnic differences will also be discussed.

Stacey A. Fedewa, Xavier Llor, Pepper Jo Schedin, Yin Cao

Cancers that are and are not increasing in younger populations

Stacey A. Fedewa

 

  • Early onset cancers, pediatric cancers and colon cancers are increasing in younger adults
  • Younger people are more likely to be uninsured and these are there most productive years so it is a horrible life event for a young adult to be diagnosed with cancer. They will have more financial hardship and most (70%) of the young adults with cancer have had financial difficulties.  It is very hard for women as they are on their childbearing years so additional stress
  • Types of early onset cancer varies by age as well as geographic locations. For example in 20s thyroid cancer is more common but in 30s it is breast cancer.  Colorectal and testicular most common in US.
  • SCC is decreasing by adenocarcinoma of the cervix is increasing in women’s 40s, potentially due to changing sexual behaviors
  • Breast cancer is increasing in younger women: maybe etiologic distinct like triple negative and larger racial disparities in younger African American women
  • Increased obesity among younger people is becoming a factor in this increasing incidence of early onset cancers

 

 

Other Articles on this Open Access  Online Journal on Cancer Conferences and Conference Coverage in Real Time Include

Press Coverage

Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Symposium: New Drugs on the Horizon Part 3 12:30-1:25 PM

Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Session on NCI Activities: COVID-19 and Cancer Research 5:20 PM

Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Session on Evaluating Cancer Genomics from Normal Tissues Through Metastatic Disease 3:50 PM

Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Session on Novel Targets and Therapies 2:35 PM

 

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Old Industrial Revolution Paradigm of Education Needs to End: How Scientific Curation Can Transform Education

Curator: Stephen J. Williams, PhD.

Dr. Cathy N. Davidson from Duke University gives a talk entitled: Now You See It.  Why the Future of Learning Demands a Paradigm Shift

In this talk, shown below, Dr. Davidson shows how our current education system has been designed for educating students for the industrial age type careers and skills needed for success in the Industrial Age and how this educational paradigm is failing to prepare students for the challenges they will face in their future careers.

Or as Dr. Davidson summarizes

Designing education not for your past but for their future

As the video is almost an hour I will summarize some of the main points below

PLEASE WATCH VIDEO

Summary of talk

Dr. Davidson starts the talk with a thesis: that Institutions tend to preserve the problems they were created to solve.

All the current work, teaching paradigms that we use today were created for the last information age (19th century)

Our job to to remake the institutions of education work for the future not the one we inherited

Four information ages or technologies that radically changed communication

  1. advent of writing: B.C. in ancient Mesopotamia allowed us to record and transfer knowledge and ideas
  2. movable type – first seen in 10th century China
  3. steam powered press – allowed books to be mass produced and available to the middle class.  First time middle class was able to have unlimited access to literature
  4. internet- ability to publish and share ideas worldwide

Interestingly, in the early phases of each of these information ages, the same four complaints about the new technology/methodology of disseminating information was heard

  • ruins memory
  • creates a distraction
  • ruins interpersonal dialogue and authority
  • reduces complexity of thought

She gives an example of Socrates who hated writing and frequently stated that writing ruins memory, creates a distraction, and worst commits ideas to what one writes down which could not be changed or altered and so destroys ‘free thinking’.

She discusses how our educational institutions are designed for the industrial age.

The need for collaborative (group) learning AND teaching

Designing education not for your past but for the future

In other words preparing students for THEIR future not your past and the future careers that do not exist today.

In the West we were all taught to answer silently and alone.  However in Japan, education is arranged in the han or group think utilizing the best talents of each member in the group.  In Japan you are arranged in such groups at an early age.  The concept is that each member of the group contributes their unique talent and skill for the betterment of the whole group.  The goal is to demonstrate that the group worked well together.

see https://educationinjapan.wordpress.com/education-system-in-japan-general/the-han-at-work-community-spirit-begins-in-elementary-school/ for a description of “in the han”

In the 19th century in institutions had to solve a problem: how to get people out of the farm and into the factory and/or out of the shop and into the firm

Takes a lot of regulation and institutionalization to convince people that independent thought is not the best way in the corporation

keywords for an industrial age

  • timeliness
  • attention to task
  • standards, standardization
  • hierarchy
  • specialization, expertise
  • metrics (measures, management)
  • two cultures: separating curriculum into STEM versus artistic tracts or dividing the world of science and world of art

This effort led to a concept used in scientific labor management derived from this old paradigm in education, an educational system controlled and success measured using

  • grades (A,B,C,D)
  • multiple choice tests

keywords for our age

  • workflow
  • multitasking attention
  • interactive process (Prototype, Feedback)
  • data mining
  • collaboration by difference

Can using a methodology such as scientific curation affect higher education to achieve this goal of teaching students to collaborate in an interactive process using data mining to create a new workflow for any given problem?  Can a methodology of scientific curation be able to affect such changes needed in academic departments to achieve the above goal?

This will be the subject of future curations tested using real-world in class examples.

However, it is important to first discern that scientific content curation takes material from Peer reviewed sources and other expert-vetted sources.  This is unique from other types of content curation in which take from varied sources, some of which are not expert-reviewed, vetted, or possibly ‘fake news’ or highly edited materials such as altered video and audio.  In this respect, the expert acts not only as curator but as referee.  In addition, collaboration is necessary and even compulsory for the methodology of scientific content curation, portending the curator not as the sole expert but revealing the CONTENT from experts as the main focus for learning and edification.

Other article of note on this subject in this Open Access Online Scientific Journal include:

The above articles will give a good background on this NEW Conceived Methodology of Scientific Curation and its Applicability in various areas such as Medical Publishing, and as discussed below Medical Education.

To understand the new paradigm in medical communication and the impact curative networks have or will play in this arena please read the following:

Scientific Curation Fostering Expert Networks and Open Innovation: Lessons from Clive Thompson and others

This article discusses a history of medical communication and how science and medical communication initially moved from discussions from select individuals to the current open accessible and cooperative structure using Web 2.0 as a platform.

 

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In Data Science, A Pioneer Practitioner’s Portfolio of Algorithm-based Decision Support Systems for Operations Management in Several Industrial Verticals: Analytics Designer, Aviva Lev-Ari, PhD, RN

An overview of Data Science as a discipline is presented in

Data Science & Analytics: What do Data Scientists Do in 2020 and a Pioneer Practitioner’s Portfolio of Algorithm-based Decision Support Systems for Operations Management in Several Industrial Verticals

 

On this landscape about IT, The Internet, Analytics, Statistics, Big Data, Data Science and Artificial Intelligence, I am to tell stories on my own pioneering work in data science, Algorithm-based decision support systems design for different organizations in several sectors of the US economy:

Images on 12/7/2019

  • Startups:
  1. TimeØ Group – The leader in Digital Marketplaces Design
  2. Concept Five Technologies, Inc. – Commercialization of DoD funded technologies
  3. MDSS, Inc. – SAAS in Analytical Services
  4. LPBI Group – Pharmaceutical & Media
  • Top Tier Management Consulting: SRI International, Monitor Group;
  • OEM: Amdahl Corporation;
  • Top 6th System Integrator: Perot System Corporation;
  • FFRDC: MITRE Corporation.
  • Publishing industry: was Director of Research at McGraw-Hill/CTB.
  • Northeastern University, Researcher on Cardiovascular Pharmacotherapy at Bouve College of Health Sciences (Independent research guided by Professor of Pharmacology)

Type of institutions:

  • For-Profit corporations: Amdahl Corp, PSC, McGraw-Hill
  • For-Profit Top Tier Consulting: Monitor Company, Now Deloitte
  • Not-for-Profit Top Tier Consulting: SRI International
  • FFRDC: MITRE
  • Pharmaceutical & Media Start up in eScientific Publishing: LPBI Group:
  1. Developers of Curation methodology for e-Articles [N = 5,700],
  2. Developers of electronic Table of Contents for e-Books in Medicine [N = 16, https://lnkd.in/ekWGNqA] and
  3. Developers of Methodologies for real time press coverage and production of e-Proceedings of Biotech Conferences [N = 70].

 

Autobiographical Annotations: Tribute to My Professors

 

Pioneering implementations of analytics to business decision making: contributions to domain knowledge conceptualization, research design, methodology development, data modeling and statistical data analysis: Aviva Lev-Ari, UCB, PhD’83; HUJI MA’76

https://pharmaceuticalintelligence.com/2018/05/28/pioneering-implementations-of-analytics-to-business-decision-making-contributions-to-domain-knowledge-conceptualization-research-design-methodology-development-data-modeling-and-statistical-data-a/

Recollections of Years at UC, Berkeley, Part 1 and Part 2

  • Recollections: Part 1 – My days at Berkeley, 9/1978 – 12/1983 – About my doctoral advisor, Allan Pred, other professors and other peers

https://pharmaceuticalintelligence.com/2018/03/15/recollections-my-days-at-berkeley-9-1978-12-1983-about-my-doctoral-advisor-allan-pred-other-professors-and-other-peer/

  • Recollections: Part 2 – “While Rolling” is preceded by “While Enrolling” Autobiographical Alumna Recollections of Berkeley – Aviva Lev-Ari, PhD’83

https://pharmaceuticalintelligence.com/2018/05/24/recollections-part-2-while-rolling-is-preceded-by-while-enrolling-autobiographical-alumna-recollections-of-berkeley-aviva-lev-ari-phd83/

Accomplishments

The Digital Age Gave Rise to New Definitions – New Benchmarks were born on the World Wide Web for the Intangible Asset of Firm’s Reputation: Pay a Premium for buying e-Reputation

For @AVIVA1950, Founder, LPBI Group @pharma_BI: Twitter Analytics [Engagement Rate, Link Clicks, Retweets, Likes, Replies] & Tweet Highlights [Tweets, Impressions, Profile Visits, Mentions, New Followers] https://analytics.twitter.com/user/AVIVA1950/tweets

Thriving at the Survival Calls during Careers in the Digital Age – An AGE like no Other, also known as, DIGITAL

Professional Self Re-Invention: From Academia to Industry – Opportunities for PhDs in the Business Sector of the Economy

Reflections on a Four-phase Career: Aviva Lev-Ari, PhD, RNMarch 2018

Was prepared for publication in American Friends of the Hebrew University (AFHU), May 2018 Newsletter, Hebrew University’s HUJI Alumni Spotlight Section.

Aviva Lev-Ari’s profile was up on 5/3/2018 on AFHU website under the Alumni Spotlight at https://www.afhu.org/

On 5/11/2018, Excerpts were Published in AFHU e-news.

https://us10.campaign-archive.com/?u=5c25136c60d4dfc4d3bb36eee&id=757c5c3aae&e=d09d2b8d72

https://www.afhu.org/2018/05/03/aviva-lev-ari/

 

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scPopCorn: A New Computational Method for Subpopulation Detection and their Comparative Analysis Across Single-Cell Experiments

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

4.2.5

4.2.5   scPopCorn: A New Computational Method for Subpopulation Detection and their Comparative Analysis Across Single-Cell Experiments, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 4: Single Cell Genomics

Present day technological advances have facilitated unprecedented opportunities for studying biological systems at single-cell level resolution. For example, single-cell RNA sequencing (scRNA-seq) enables the measurement of transcriptomic information of thousands of individual cells in one experiment. Analyses of such data provide information that was not accessible using bulk sequencing, which can only assess average properties of cell populations. Single-cell measurements, however, can capture the heterogeneity of a population of cells. In particular, single-cell studies allow for the identification of novel cell types, states, and dynamics.

One of the most prominent uses of the scRNA-seq technology is the identification of subpopulations of cells present in a sample and comparing such subpopulations across samples. Such information is crucial for understanding the heterogeneity of cells in a sample and for comparative analysis of samples from different conditions, tissues, and species. A frequently used approach is to cluster every dataset separately, inspect marker genes for each cluster, and compare these clusters in an attempt to determine which cell types were shared between samples. This approach, however, relies on the existence of predefined or clearly identifiable marker genes and their consistent measurement across subpopulations.

Although the aligned data can then be clustered to reveal subpopulations and their correspondence, solving the subpopulation-mapping problem by performing global alignment first and clustering second overlooks the original information about subpopulations existing in each experiment. In contrast, an approach addressing this problem directly might represent a more suitable solution. So, keeping this in mind the researchers developed a computational method, single-cell subpopulations comparison (scPopCorn), that allows for comparative analysis of two or more single-cell populations.

The performance of scPopCorn was tested in three distinct settings. First, its potential was demonstrated in identifying and aligning subpopulations from single-cell data from human and mouse pancreatic single-cell data. Next, scPopCorn was applied to the task of aligning biological replicates of mouse kidney single-cell data. scPopCorn achieved the best performance over the previously published tools. Finally, it was applied to compare populations of cells from cancer and healthy brain tissues, revealing the relation of neoplastic cells to neural cells and astrocytes. Consequently, as a result of this integrative approach, scPopCorn provides a powerful tool for comparative analysis of single-cell populations.

This scPopCorn is basically a computational method for the identification of subpopulations of cells present within individual single-cell experiments and mapping of these subpopulations across these experiments. Different from other approaches, scPopCorn performs the tasks of population identification and mapping simultaneously by optimizing a function that combines both objectives. When applied to complex biological data, scPopCorn outperforms previous methods. However, it should be kept in mind that scPopCorn assumes the input single-cell data to consist of separable subpopulations and it is not designed to perform a comparative analysis of single cell trajectories datasets that do not fulfill this constraint.

Several innovations developed in this work contributed to the performance of scPopCorn. First, unifying the above-mentioned tasks into a single problem statement allowed for integrating the signal from different experiments while identifying subpopulations within each experiment. Such an incorporation aids the reduction of biological and experimental noise. The researchers believe that the ideas introduced in scPopCorn not only enabled the design of a highly accurate identification of subpopulations and mapping approach, but can also provide a stepping stone for other tools to interrogate the relationships between single cell experiments.

References:

https://www.sciencedirect.com/science/article/pii/S2405471219301887

https://www.tandfonline.com/doi/abs/10.1080/23307706.2017.1397554

https://ieeexplore.ieee.org/abstract/document/4031383

https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-0927-y

https://www.sciencedirect.com/science/article/pii/S2405471216302666

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Real Time Coverage @BIOConvention #BIO2019: Precision Medicine Beyond Oncology June 5 Philadelphia PA

Reporter: Stephen J Williams PhD @StephenJWillia2

Precision Medicine has helped transform cancer care from one-size-fits-all chemotherapy to a new era, where patients’ tumors can be analyzed and therapy selected based on their genetic makeup. Until now, however, precision medicine’s impact has been far less in other therapeutic areas, many of which are ripe for transformation. Efforts are underway to bring the successes of precision medicine to neurology, immunology, ophthalmology, and other areas. This move raises key questions of how the lessons learned in oncology can be used to advance precision medicine in other fields, what types of data and tools will be important to personalizing treatment in these areas, and what sorts of partnerships and payer initiatives will be needed to support these approaches and their ultimate commercialization and use. The panel will also provide an in depth look at precision medicine approaches aimed at better understanding and improving patient care in highly complex disease areas like neurology.
Speaker panel:  The big issue now with precision medicine is there is so much data and hard to put experimental design and controls around randomly collected data.
  • The frontier is how to CURATE randomly collected data to make some sense of it
  • One speaker was at a cancer meeting and the oncologist had no idea what to make of genomic reports they were given.  Then there is a lack of action or worse a misdiagnosis.
  • So for e.g. with Artificial Intelligence algorithms to analyze image data you can see things you can’t see with naked eye but if data quality not good the algorithms are useless – if data not curated properly data is wasted
Data needs to be organized and curated. 
If relying of AI for big data analysis the big question still is: what are the rates of false negative and false positives?  Have to make sure so no misdiagnosis.

Please follow LIVE on TWITTER using the following @ handles and # hashtags:

@Handles

@pharma_BI

@AVIVA1950

@BIOConvention

# Hashtags

#BIO2019 (official meeting hashtag)

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Thriving at the Survival Calls during Careers in the Digital Age – An AGE like no Other, also known as, DIGITAL, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 1: Next Generation Sequencing (NGS)

Thriving at the Survival Calls during Careers in the Digital Age – An AGE like no Other, also known as, DIGITAL

Author and Curator: Aviva Lev-Ari, PhD, RN

 

The source for the inspiration to write this curation is described in

Survival Calls during Careers in the Digital Age

https://pharmaceuticalintelligence.com/2018/06/13/survival-calls-during-careers-in-the-digital-age/

 

In this curation, I present the following concepts in three parts:

  1. Part 1: Authenticity of Careers in the Digital Age: In Focus, the BioTechnology Sector
  2. Part 2: Top 10 books to help you survive the Digital Age

  3. Part 3: A case study on Thriving at the Survival Calls during Careers in the Digital Age: Aviva Lev-Ari, UCB, PhD’83; HUJI, MA’76 

 

Part 1: Authenticity of Careers in the Digital Age: 

In Focus, the BioTechnology Sector

 

Lisa LaMotta, Senior Editor, BioPharma Dive wrote in Conference edition | June 11, 2018

Unlike that little cancer conference in Chicago last week, the BIO International convention is not about data, but about the people who make up the biopharma industry.

The meeting brings together scientists, board members, business development heads and salespeople, from the smallest virtual biotechs to the largest of pharmas. It allows executives at fledgling biotechs to sit at the same tables as major decision-makers in the industry — even if it does look a little bit like speed dating.

But it’s not just a partnering meeting.

This year’s BIO also sought to shine a light on pressing issues facing the industry. Among those tackled included elevating the discussion on gender diversity and how to bring more women to the board level; raising awareness around suicide and the need for more mental health treatments; giving a voice to patient advocacy groups; and highlighting the need for access to treatments in developing nations.

Four days of meetings and panel discussions are unlikely to move the needle for many of these challenges, but debate can be the first step toward progress.

I attended the meetings on June 4,5,6, 2018 and covered in Real Time the sessions I attended. On the link below, Tweets, Re-Tweets and Likes mirrors the feelings and the opinions of the attendees as expressed in real time using the Twitter.com platform. This BioTechnology events manifested the AUTHENTICITY of Careers in the Digital Age – An AGE like no Other, also known as, DIGITAL.

The entire event is covered on twitter.com by the following hash tag and two handles:

 

I covered the events on two tracks via two Twitter handles, each handle has its own followers:

The official LPBI Group Twitter.com account

The Aviva Lev-Ari, PhD, RN Twitter.com account

Track A:

  • Original Tweets by @Pharma_BI and by @AVIVA1950 for #BIO2018 @IAmBiotech @BIOConvention – BIO 2018, Boston, June 4-7, 2018, BCEC

Curator: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2018/06/11/original-tweets-by-pharma_bi-and-by-aviva1950-from-bio2018-iambiotech-bioconvention-bio-2018-boston-june-4-7-2018-bcec/

 

  • Reactions to Original Tweets by @Pharma_BI and by @AVIVA1950 from #BIO2018

Curator: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2018/06/12/reactions-to-original-tweets-by-pharma_bi-and-by-aviva1950-from-bio2018/

Track B:

  • Re-Tweets and Likes by @Pharma_BI and by @AVIVA1950 from #BIO2018 @IAmBiotech @BIOConvention – BIO 2018, Boston, June 4-7, 2018, BCEC

Curator: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2018/06/11/re-tweets-and-likes-by-pharma_bi-aviva1950-from-bio2018-iambiotech-bioconvention-bio-2018-boston-june-4-7-2018-bcec/

Part 2: Top 10 books to help you survive the digital age

From Philip K Dick’s obtuse robots to Mark O’Connell’s guide to transhumanism, novelist Julian Gough picks essential reading for a helter skelter world

Here are 10 of the books that did help me [novelist Julian Gough]: they might also help you understand, and survive, our complicated, stressful, digital age.

  1. Marshall McLuhan Unbound by Marshall McLuhan (2005)
    The visionary Canadian media analyst predicted the internet, and coined the phrase the Global Village, in the early 1960s. His dense, complex, intriguing books explore how changes in technology change us. This book presents his most important essays as 20 slim pamphlets in a handsome, profoundly physical, defiantly non-digital slipcase.
  2. Ubik by Philip K Dick (1969)
    Pure pulp SF pleasure; a deep book disguised as a dumb one. Dick shows us, not a dystopia, but a believably shabby, amusingly human future. The everyman hero, Joe Chip, wakes up and argues with his robot toaster, which refuses to toast until he sticks a coin in the slot. Joe can’t do this, because he’s broke. He then has a stand-up row with his robot front door, which won’t open, because he owes it money too … Technology changes: being human, and broke, doesn’t. Warning: Dick wrote Ubik at speed, on speed. But embedded in the pulpy prose are diamonds of imagery that will stay with you for ever.
  3. The Singularity Is Near by Ray Kurzweil (2005)
    This book is what Silicon Valley has instead of a bible. It’s a visionary work that predicts a technological transformation of the world in our lifetime. Kurzweil argues that computer intelligence will soon outperform human thought. We will then encode our minds, upload them, and become one with our technology, achieving the Singularity. At which point, the curve of technological progress starts to go straight up. Ultimately – omnipotent, no longer mortal, no longer flesh – we transform all the matter in the universe into consciousness; into us.
  4. To Be a Machine by Mark O’Connell (2017)
    This response to Kurzweil won this year’s Wellcome prize. It’s a short, punchy tour of transhumanism: the attempt to meld our minds with machines, to transcend biology and escape death. He meets some of the main players, and many on the fringes, and listens to them, quizzically. It is a deliberately, defiantly human book, operating in that very modern zone between sarcasm and irony, where humans thrive and computers crash.
  5. A Visit from the Goon Squad by Jennifer Egan (2011)
    This intricately structured, incredibly clever novel moves from the 60s right through to a future maybe 15 years from now. It steps so lightly into that future you hardly notice the transition. It has sex and drugs and rock’n’roll, solar farms, social media scams and a stunningly moving chapter written as a PowerPoint presentation. It’s a masterpiece. Life will be like this.
  6. What Technology Wants by Kevin Kelly (2010)
    Kelly argues that we scruffy biological humans are no longer driving technological progress. Instead, the technium, “the greater, global, massively interconnected system of technology vibrating around us”, is now driving its own progress, faster and faster, and we are just caught up in its slipstream. As we accelerate down the technological waterslide, there is no stopping now … Kelly’s vision of the future is scary, but it’s fun, and there is still a place for us in it.
  7. The Meme Machine by Susan Blackmore (1999)
    Blackmore expands powerfully and convincingly on Richard Dawkins’s original concept of the meme. She makes a forceful case that technology, religion, fashion, art and even our personalities are made of memes – ideas that replicate, mutate and thus evolve over time. We are their replicators (if you buy my novel, you’ve replicated its memes); but memes drive our behaviour just as we drive theirs. It’s a fascinating book that will flip your world upside down.
  8. Neuromancer by William Gibson (1984)
    In the early 1980s, Gibson watched kids leaning into the screens as they played arcade games. They wanted to be inside the machines, he realised, and they preferred the games to reality. In this novel, Gibson invented the term cyberspace; sparked the cyberpunk movement (to his chagrin); and vividly imagined the jittery, multi-screened, anxious, technological reality that his book would help call into being.
  9. You Are Not a Gadget: A Manifesto by Jaron Lanier (2010)
    Lanier, an intense, brilliant, dreadlocked artist, musician and computer scientist, helped to develop virtual reality. His influential essay Digital Maoism described early the downsides of online collective action. And he is deeply aware that design choices made by (mainly white, young, male) software engineers can shape human behaviour globally. He argues, urgently, that we need to question those choices, now, because once they are locked in, all of humanity must move along those tracks, and we may not like where they take us. Events since 2010 have proved him right. His manifesto is a passionate argument in favour of the individual voice, the individual gesture.
  10. All About Love: New Visions by bell hooks (2000)
    Not, perhaps, an immediately obvious influence on a near-future techno-thriller in which military drones chase a woman and her son through Las Vegas. But hooks’s magnificent exploration and celebration of love, first published 18 years ago, will be far more useful to us, in our alienated digital future, than the 10,000 books of technobabble published this year. All About Love is an intensely practical roadmap, from where we are now to where we could be. When Naomi and Colt find themselves on the run through a militarised American wilderness of spirit, when GPS fails them, bell hooks is their secret guide.

SOURCE

https://www.theguardian.com/books/2018/may/30/top-10-books-to-help-you-survive-the-digital-age?utm_source=esp&utm_medium=Email&utm_campaign=Bookmarks+-+Collections+2017&utm_term=277690&subid=25658468&CMP=bookmarks_collection

Part 3: A case study on Thriving at the Survival Calls during Careers in the Digital Age:  Aviva Lev-Ari, UCB, PhD’83; HUJI, MA’76

 

On June 10, 2018

 

Following, is a case study about an alumna of HUJI and UC, Berkeley as an inspirational role model. An alumna’s profile in context of dynamic careers in the digital age. It has great timeliness and relevance to graduate students, PhD level at UC Berkeley and beyond, to all other top tier universities in the US and Europe. As presented in the following curations:

Professional Self Re-Invention: From Academia to Industry – Opportunities for PhDs in the Business Sector of the Economy

https://pharmaceuticalintelligence.com/2018/05/22/professional-self-re-invention-from-academia-to-industry-opportunities-for-phds-in-the-business-sector-of-the-economy/

 

Pioneering implementations of analytics to business decision making: contributions to domain knowledge conceptualization, research design, methodology development, data modeling and statistical data analysis: Aviva Lev-Ari, UCB, PhD’83; HUJI, MA’76 

https://pharmaceuticalintelligence.com/2018/05/28/pioneering-implementations-of-analytics-to-business-decision-making-contributions-to-domain-knowledge-conceptualization-research-design-methodology-development-data-modeling-and-statistical-data-a/

 

This alumna is Editor-in-Chief of a Journal that has other 173 articles on Scientist: Career Considerations 

https://pharmaceuticalintelligence.com/category/scientist-career-considerations/

 

In a 5/22/2018 article, Ways to Pursue Science Careers in Business After a PhD by Ankita Gurao,

https://bitesizebio.com/38498/ways-to-pursue-the-business-of-science-after-a-ph-d/?utm_source=facebook&utm_medium=social&utm_campaign=SocialWarfare

Unemployment figures of PhDs by field of science are included, Ankita Gurao identifies the following four alternative careers for PhDs in the non-academic world:

  1. Science Writer/Journalist/Communicator
  2. Science Management
  3. Science Administration
  4. Science Entrepreneurship

My career, as presented in Reflections on a Four-phase Career: Aviva Lev-Ari, PhD, RN, March 2018

https://pharmaceuticalintelligence.com/2018/03/06/reflections-on-a-four-phase-career-aviva-lev-ari-phd-rn-march-2018/

has the following phases:

  • Phase 1: Research, 1973 – 1983
  • Phase 2: Corporate Applied Research in the US, 1985 – 2005
  • Phase 3: Career Reinvention in Health Care, 2005 – 2012
  • Phase 4: Electronic Scientific Publishing, 4/2012 to present

These four phases are easily mapped to the four alternative careers for PhDs in the non-academic world. One can draw parallel lines between the four career opportunities A,B,C,D, above, and each one of the four phases in my own career.

Namely, I have identified A,B,C,D as early as 1985, and pursued each of them in several institutional settings, as follows:

A. Science Writer/Journalist/Communicator – see link above for Phase 4: Electronic Scientific Publishing, 4/2012 to present 

B. Science Management – see link above for Phase 2: Corporate Applied Research in the US, 1985 – 2005 and Phase 3: Career Reinvention in Health Care, 2005 – 2012 

C. Science Administration – see link above for Phase 2: Corporate Applied Research in the US, 1985 – 2005and Phase 4: Electronic Scientific Publishing, 4/2012 to present 

D. Science Entrepreneurship – see link above for Phase 4: Electronic Scientific Publishing, 4/2012 to present  

Impressions of My Days at Berkeley in Recollections: Part 1 and 2, below.

  • Recollections: Part 1 – My days at Berkeley, 9/1978 – 12/1983 –About my doctoral advisor, Allan Pred, other professors and other peers

https://pharmaceuticalintelligence.com/2018/03/15/recollections-my-days-at-berkeley-9-1978-12-1983-about-my-doctoral-advisor-allan-pred-other-professors-and-other-peer/

  • Recollections: Part 2 – “While Rolling” is preceded by “While Enrolling” Autobiographical Alumna Recollections of Berkeley – Aviva Lev-Ari, PhD’83

https://pharmaceuticalintelligence.com/2018/05/24/recollections-part-2-while-rolling-is-preceded-by-while-enrolling-autobiographical-alumna-recollections-of-berkeley-aviva-lev-ari-phd83/

The topic of Careers in the Digital Age is closely related to my profile, see chiefly: Four-phase Career, Reflections, Recollections Parts 1 & 2 and information from other biographical sources, below.

Other sources for my biography

 

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Pioneering implementation of analytics to business decision making: contributions to domain knowledge conceptualization, research design, methodology development, data modeling and statistical data analysis: Aviva Lev-Ari, UCB, PhD’83; HUJI, MA’76

Author: Aviva Lev-Ari, PhD, RN 

May 24, 2018

April 12. 2017

INTRODUCTION

In 1975, while a Masters student at the Hebrew University in Jerusalem (HUJI), I attended a graduate course, “Methodology Development and Theory Construction in the Social Sciences”. The course was taught by Prof. Louis Guttman. He arrived in Israel in 1948 from Cornell University to establish the measurement concentration in cognitive sciences in the psychology department at HUJI. He established the Applied Research Institute in Social Sciences, where public opinion studies were carried out for fifty years. Dr. Shlomit Levy, a key collaborator of Prof. Guttman, was the teaching assistant for the class. Every Masters student across all the departments of the social sciences faculty, planning to write a Master thesis enrolled in this course, one semester for five hours a week.

It had two major project submissions and two exams. It was considered the most difficult course at HUJI. I got [A minus] and was stimulated and attracted to the course domain for the 25 years that followed.

Following this course, I attended an advanced course by Professor Chaim Adler:

http://taubcenter.org.il/chaim-adler/,

in the Department of Sociology on multivariate analysis, and have used ADDTREE, a software developed by Prof. Amos Tversky and his programmer, a PhD student in the mathematics department at HUJI, Shmuel Sattath, who assisted me with SPSS on my Master thesis data base, which had 200 subjects and 42 variables and was considered a large data set for SPSS in 1975. Mr. Sattath recommended ADDTREE. The programming functions were taken over by Amnon Antebi, who worked with me on MSA, POSA, and ADDTREE, carrying two heavy boxes of computer punched cards for the CDC mainframe computer at the Center for Computation at HUJI. Antebi, as a professional mainframe computer programmer, alone could submit jobs and pick up the printed output, which was placed in bins alphabetically by the last name of the programmer.

Professor Louis Guttman was the developer of the Guttman scale, MDS: MSA, SSA, and POSA, and many other algorithms used originally in psychometrics since 1880. The field is concerned with the objective measurement of skills and knowledge, abilities, attitudes, personality traits, and educational achievement. Assessment tools such as questionnaires, tests, raters’ judgments, and personality tests were constructed and adopted, and these became the foundation of quantitative modeling in the social sciences since the 1930s.

Guttman was a member of the Israel Academy of Sciences and Humanities, a foreign honorary member of the American Academy of Arts and Sciences, and president of the Psychometric Society. In 1956 he was a fellow at the Center for Advanced Study in the Behavioral Sciences; in 1962 he received the Rothschild Prize. The development of scaling theory by Louis Guttman and Clyde Coombs has been recognized by Science as one of 62 major advances in the social sciences in the period 1900-1965.[1] Other awards were:

Guttman died on October 25, 1987, while on sabbatical leave in Minneapolis.

https://wikivividly.com/wiki/Louis_Guttman

In this course I learned MDS: MSA, SSA, POSA and to design questionnaires. I designed one for my Masters thesis and applied it to two samples with 100 heads of household in each sample. I applied the Kolmogorov-Smirnov test for a two-sample comparison and applied the ADDTREE clustering algorithm to compare the results of dimensionality reduction of 42 variables by MDS vs ADDTREE, This was the first application of

  • ADDTREE software to consumer preferences
  • MDS to consumer choice under constraints

The thesis grade contributed to the final Master GPA. I was told by the graduate office that my GPA was the highest grade ever awarded for a Masters degree in social sciences at HUJI until 1976.

Of all the courses I took at HUJI during the six years of my enrollment for a BA and an MA – it was Prof. Guttman and Prof. Adler’s courses that set off my career in quantitative methods from the start of the Masters thesis for the next 25 years, performing creative data modeling and analysis as a profession.

While working at SRI, I contacted Yissum, the HUJI’s technology transfer office (TTO) for licensing the MDS software, written by Reuven Amar, at SRI International. We applied MSA and SSA on GM data and in several other studies. This was the second time that I licensed the software from HUJI.

I cherish the correspondence I had with Prof. Louis Guttman following my hiring at SRI International. He was very proud to know that his student was using MSA for General Motors management decision making on selective divestiture of their auto parts division. He knew SRI International, as an R&D institution, very well for its projects in education, biostatistics and genetics (his wife, Prof. Ruth Guttman, was professor of Genetics at Cornell and HUJI.)

I visited him in 1986 in Jerusalem, showing him the computer output of the data from the GM project. Of course, he had important insights into the interpretation of the results. I sent him a copy of a professional movie made on the GM model that I designed. The VCR cassette was returned to me by his daughter in New Jersey following his death, 10/25/1987. He received it at the hospital. He knew about it but was unable to watch the movie, I was told.

The first time I licensed the MDS software from Yissum, was for teaching purposes at UC Berkeley, 1979, 1980, and 1981.

Upon my admission to the PhD Program at UC Berkeley, Prof. Pred arranged for me a teaching assistantship for an upper division course, three semesters in Quantitative Methods. This was the last course before graduation for any concentration in Letters & Sciences. The course was attended by students from geography, political sciences, political economics, economics, archeology, city planning, and botany. Any student that wished to learn about multivariate classification and prediction modeling enrolled.

It was a great privilege to write recommendation letters in February for a student graduating in May 1982. Some told me that “this is the only course that will get me a job.” It turned out that, that was true for myself as well, referring to Prof. Guttman’s course. Following the graduation from the Masters program at HUJI, I was hired at the Technion, IIT, because I mastered non-linear modeling and in particular MDS: MSA, SSA, and POSA.

During my career, I had the opportunity to design numerous one-of-a-kind models which represent pioneering implementations of analytics. A complete list is documented in the sources, below (List of Publications, 1983-2004). The very salient ones that represent milestones in the profession and the first application of these algorithms in these specific domain knowledge, include the following selective list:

  • Application of Multidimensional Scaling (MDS) for decomposition of consumer multivariate preference function, Master thesis, HUJI, 1976
  • Application of Multidimensional Scaling (MDS) for classification of urban municipalities in Israel for resource allocation of Ministry of Transportation road safety budget, Technion, TRC, RSC, 1977-1978
  • Multivariate analysis of product portfolios across 27 leading American paper companies for industrial concentration assessment and corporate benchmarking in sector context. PhD dissertation, UC Berkeley, 1983.
  • Application of Multidimensional Scaling (MDS) for SRI International’s clients: Competitive Assessment: Automotive. That contribution is mentioned in the 1987 Annual Report. Technology Assessment: Chemical and Allied Products, Resource Allocation Modeling in Advanced Material, Credit Scoring problem for clients in the Financial Sectors: Banking & Insurance
  • Demand Forecasting Model for Hardware, Amdahl Corporation. This model led to 1989 Employee Award.
  • Design of a Digital Market Place for Analytical Services at Concept Five Technologies, Inc.1996.
  • Design of Analytics suite of services for Digital Marketplaces: lumber, hospital supplies, MRO and consumables, PSC, 2007-2001. This modeling effort led to a distinguish bonus award,1999.
  • Adaptive Testing at McGraw-Hill, 2002, application of inverted simulation annealing algorithm for prediction of maximum functions in achievement scores.

 

HIGHLIGHTS

 

APPOINTMENTS – Director level, Advanced Analytics

In 25 years of working in corporate America for companies that are #1 in their sector, I received and accepted eleven job offers!

Chiefly,

  • SRI International, Menlo Park, CA – Largest THINK TANK in the US

Title: Director Business & Economic Statistics

  • Amdahl Corporation, Sunnyvale, CA  – 3rd largest mainframe computer company in the world, acquired by Fujitzu

Title: Manager, Demand Forecasting and Modeling

  • Monitor Group, Cambridge, MA – Top Tier Management Consulting, acquired by Deloitte

Title: Senior Methodology Consultant, Financial Sector

  • MITRE, Bedford, MA – largest federally funded R&D corporation and its spin-offs:

Title at MITRE: Head of Research, Economic & Decision Analysis Center

Title at MITRETEKDirector of Analytics

Title at Concept Five Technologies, Inc.: Director, Advanced Information Systems

  • Perot Systems Corporation, Cambridge, MA – Top IT outsourcer, acquired by Dell Computers

Title: Director, Advanced Analytics Digital Marketplaces

  • McGraw-Hill/CTB, Monterey, CA – world’s oldest publisher

Title: Director of Research: Methods and Applications

 

BUILDING PROFESSIONAL EXPERTISE IN APPLICATION of QUANTITATIVE METHODS FOR CORPORATE DECISION MAKING BASED OF DATA SCIENCE

A Twenty Five year Career in Data Science

Data Science is the Greatest Science! It is the Greatest Science for Women, as well

https://pharmaceuticalintelligence.com/2018/03/12/data-science-is-the-greatest-science-it-is-the-greatest-science-for-women-as-well/

Professional Self Re-Invention: From Academia to Industry – Opportunities for PhDs in the Business Sector of the Economy

https://pharmaceuticalintelligence.com/2018/05/22/professional-self-re-invention-from-academia-to-industry-opportunities-for-phds-in-the-business-sector-of-the-economy/

In a 5/22/2018 article, Ways to Pursue Science Careers in Business After a PhD By ankita gurao,

https://bitesizebio.com/38498/ways-to-pursue-the-business-of-science-after-a-ph-d/?utm_source=facebook&utm_medium=social&utm_campaign=SocialWarfare

Unemployment figures of PhDs by field of science are included, Ankita Gurao identifies the following four alternative careers for PhDs in the non-academic world:

A. Science Writer/Journalist/Communicator

B. Science Management

C. Science Administration

D. Science Entrepreneurship

My career, as presented in Reflections on a Four-phase Career: Aviva Lev-Ari, PhD, RN, March 2018

https://pharmaceuticalintelligence.com/2018/03/06/reflections-on-a-four-phase-career-aviva-lev-ari-phd-rn-march-2018/

has the following phases:

  • Phase 1: Research, 1973 – 1983
  • Phase 2: Corporate Applied Research in the US, 1985 – 2005
  • Phase 3: Career Reinvention in Health Care, 2005 – 2012
  • Phase 4: Electronic Scientific Publishing, 4/2012 to Present

These four phases are easily mapped to the four alternative careers for PhDs in the non-academic world. One can draw parallels between the four career opportunities A,B,C,D, above, and each one of the four phases in my own career.

Namely, I have identified A,B,C,D as early as 1985, and pursued each of them in several institutional settings, as follows:

A. Science Writer/Journalist/Communicator – see link above for Phase 4: Electronic Scientific Publishing, 4/2012 to Present 

B. Science Management – see link above for Phase 2: Corporate Applied Research in the US, 1985 – 2005 and Phase 3: Career Reinvention in Health Care, 2005 – 2012 

C. Science Administration – see link above for Phase 2: Corporate Applied Research in the US, 1985 – 2005 and Phase 4: Electronic Scientific Publishing, 4/2012 to Present 

D. Science Entrepreneurship – see link above for Phase 4: Electronic Scientific Publishing, 4/2012 to Present

 

SOURCES

List of Publications, 1983 – 2004

https://pharmaceuticalintelligence.com/founder/list-of-publications-1983-2004/

List of Invited Lectures, 1983 -2004

https://pharmaceuticalintelligence.com/founder/list-of-invited-lectures-1983-2004/

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