Leaders in Pharmaceutical Business Intelligence (LPBI) Group

LPBI Text Analysis Comprehensive Tutorial URL:

https://docs.google.com/document/d/1NrRG0FgRxa9oUbTl6wEIrIUhk66aIs6vdBFowr06L6g/edit?usp=sharing

LPBI Text Analysis PowerPoint Visualizations URL:

https://docs.google.com/presentation/d/15hfyW_4u7bbDmrPlpfKhEKG0fgrump3lJjstOMyAjEw/edit?usp=sharing

IRINA created DROPBOX Folder for each Intern – each person’s name

https://www.dropbox.com/sh/vfkqxsj56uqpw3s/AADskZtMurRsEzz4OK-SXWu4a?dl=0

MADISON created a TEMPLATE for all INTERNS to use

https://drive.google.com/drive/folders/1tihvZa_hmefJadr7Qelc1DCn626IdLM7

2021 Academic Internship in

Medical Text Analysis (MTA)

with

Natural Language Processing (MTA-NLP)

9/2020 – 9/2021

INTERNSHIPS in LIFE SCIENCES,

Medicine, Biological Sciences, Drug Discovery 

Intended for STEM Students at ALL education level – tasks adjusted per academics

12th Grade CODING Students

College Students in the Life Sciences

PostDocs in Biological Sciences

CONTACT:

 avivalev-ari@alum.berkeley.edu

UPDATED on 3/30/2021

“There is tremendous excitement right now for open source NLP and for producing useful models outside of big tech companies.” says Alexander Rush, a computer science professor at Cornell University, referring to a subfield of AI known as natural language processing that’s focused on helping machines use language. “There is something akin to an NLP space race going on.”

If that’s the case, then GPT-3 might be considered the field’s Sputnik. GPT-3 consists of an enormous artificial neural network that was fed many billions of words of text scraped from the web. GPT-3 can be startlingly eloquent and articulate, although it can also spurt out gibberish and offensive statements. Dozens of research groups and companies are seeking ways to make use of the technology.

The code for GPT-3 has not been released, but the few dozen researchers behind Eleuther, who come from across academia and industry, are drawing on papers that describe how it works.

Rush, who isn’t affiliated with Eleuther, says the project is one of the most impressive of a growing number of open source efforts in NLP. Besides releasing powerful language algorithms modeled after GPT-3, he says the Eleuther team has curated and released a high-quality text data set known as the Pile for training NLP algorithms.

The Eleuther project makes use of distributed computing resources, donated by cloud company CoreWeave as well as Google, through the TensorFlow Research Cloud, an initiative that makes spare computer power available, according to members of the project. To ease access to computer power, the Eleuther team created a way to split AI computations across multiple machines. But it isn’t clear how the computational requirements might be met if the project continues to grow.

OpenAI is betting that GPT-3 can be commercialized. In July 2019, OpenAI received a $1 billion investment from Microsoft, which a year later got exclusive rights to license GPT-3. OpenAI says that over 300 GPT-3 projects are in the works, using a limited-access API. These include a tool for drawing insights from customer feedback, a system that auto-generates emails from bullet points, and never-ending text-based adventure games. Eleuther might make it easier to build similar tools without access to the GPT-3 API.

UPDATED on 3/28/2021

For 4/15/2021 at 10 AM EST – Meeting with LINGUAMATICS:

1. Danielle (had confirmed) will present 10, below for Chapter 2 in Cancer Volume 1, means 8 & 9, below on ALL articles
2. Madison, Please CONFIRM, will present 10, below for 17 Cancer articles provided by Dr. Williams, means 8 & 9, below on ALL articles 
3. If Madison and Danielle are not available to present THEN Dr. Williams will present

• All Team Members: Please create ONE Folder for EACH Chapter for the book(s) each is working on
• This Folder will comprise of the following 14 item 

Following is the workflow for MEDICAL TEXT ANALYSIS for be followed by the Team:

Thanks to Amandeep Kaur for streamlining the workflow, 1-10 from a previous e-mail sent to all

1.  One MS Word file for All Articles in a chapter – Chapter’s subject CONTEXT as UNIT CASE for Text Analysis by NLP

2.  One Text file for All Articles in a chapter – to be used for Wolfram NLP

3.  One MS Word File Containing All the Biological Images with Article Name, Author, URL of All Articles in a chapter – to be use for uploading images to the Gallery of the NEW WEBSITE for 2.0 LPBI [under construction]

4.  One MS Word file per Article  – to be INDEXED for Blockchain Transactions Network

5.  One Text file per Article – to be used for 2, above

6.  One WordCloud per Article – Test Analysis visual #1

7.  One Bar Diagram from Above option 1 (means All Articles) – Test Analysis visual #2

7.1  One Bar Diagram produced from 2, above – Text Analysis visual # 2.1 – Word frequency for Subject Context of the Chapter 

8.  One Wolfram Hyper-graph from Above option 1 (means All Articles) – Test Analysis visual #3

9.  One Tree Diagram from Above option 1 (means All Articles) – Test Analysis visual #4

10.  One PowerPoint Presentation PER CHAPTER containing WordClouds, bar diagrams, hyper-graphs, tree diagrams of i.e., Genomic Vol 1 (means All chapters) – Test Analysis visual #5

11.  Domain Knowledge Expert Interpretations in English Text for 8, above – Test Analysis Interpretation of Hyper-graph in English Text File #6 [Place holder for Dr. Williams]

12.  Domain Knowledge Expert Interpretations in English Text for 9, above – Test Analysis Interpretation of Tree Diagram in English Text File #7 [Place holder for Dr. Williams]

13.  Translation of 11, above [Interpretation of Hyper-graph] into three languages each – Test Analysis Translation Texts

#8, #9, #10 [three place holders]

14.  Translation of 12, above [Interpretation of Tree diagram] into three languages each – Test Analysis Translation Texts #11, #12, #13 [three place holders]

UPDATED on 3/3/2021

     Since 2012, Leaders in Pharmaceutical Business Intelligence Group (“LPBI Group”) is a leading, electronic scientific content-creation venture, offering real-time, original scientific content through advanced platform architecture and curation methodologies applied to content in Medicine, Life Sciences, Health Care and Pharmaceutical. 

The company’s commitment is to synthesize, analyze and interpret complex, medical and scientific disease information through electronic publishing venues via the cloud to advance the knowledge and research efforts of the scientific and business community. LPBI is recognized as an online leader in scientific curation and dissemination, scientific communication, and medical & pharmaceutical information analysis. Over these years the LPBI Group has generated several large databases of biomedical information, highly curated by teams of scientific and medical experts.  These corpuses of knowledge consist of four main sources of biomedical text including:

1) a series of 18 BioMed e-books on cancer, genomics, cardiovascular diseases, metabolomics, immunology, infectious diseases and precision medicine.   

2) an Open Access Online Scientific Journal consisting of +6,000 articles in over 730 categories of research, based on an ontology created by the domain knowledge experts of the LPBI Group 

3) a corpus of over 70 e-Proceedings of leading Global Scientific/Medical Conferences, reported and curated based on a methodology developed by the LPBI Group producing with one click the digital document, aka e-Proceedings of the conferences and Tweet collections digital documents of all the tweets posted during the last 36 events we covered by LPBI members of the team functioning as Press on behalf of the Conferences organizers.

4) a Gallery of 5,100 Biological Images that populate the +6,000 scientific articles. Each Image has a text legend, and often text is typed on the images to designate details portrayed on the image. Images source is in text format as well. 

We are now developing a new platform, based on Blockchain technology, to allow Knowledge Workers to access, use and analyze our extensive structured knowledge databases mentioned in 1,2,3,4, above. 

We are seeking Academic partners who can provide natural language processing advice and capabilities for the process of Medical Text Analysis with NLP and Deep Learning. The visualization and other digital products generated by the NLP process for each article and for collections of articles, I.e., 

A. all articles in a Chapter in a Book, and/or 

B. all or a selection of Top n articles, rank ordered by # of views from all articles in one or more of the 730 categories of research assigned as main category by the author for the article fetched in the search submitted by a Knowledge Worker accessing LPBI Blockchain interface in the digital store of the premier Health Care Digital Marketplace designed and operated by an IT vendor based in Denver, CO. This vendor is designing LPBI’s Digital Store by our specifications, this design involve embedding of NLP in the blockchain API layer(s).

This new platform under design will allow scalability for the ever-increasing knowledge set we are generating. 

• The text of an existing article is subjected for test analysis with NLP.
• The process generates additional blocks in the article profile:

(1) WordCloud as Abstract

(2) Bar diagram of word frequencies

(3) hyper-graph(s) and

(4) Tree diagram(s) for A and B, above and

(5) Domain knowledge expert INTERPRETATION of the visualization.

(6) Ability to specify getting this interpretation in English text format and/or getting it in several Foreign languages text.

• Content monetization take place by filling up a FORM with all the selections for content download options:

(a) the original article,

(b) one or n articles from the article set presented by the Recommendation Engine,

(c) original images and NLP generated visuals

(d) NLP results interpretation by domain knowledge experts

(e) choice of English or several Foreign  languages for the text of these interpretations

• Features of the Blockchain Transactions Network will include: Permissions, Immutable LEDGER for the payments taking place prior to Permission grants to download contents, Smart contracts, Cybersecurity of the IP

We have successfully beta tested NLP algorithms on small-representative, structured datasets of articles, Text files and  Biological images files. 

• This proof-of-concept is now expected to compare the results LPBI generated by using Wolfram NLP Language for Biological Sciences vs the results now being produced by LINGUAMATICS, a lead NLP vendor for the Pharma industry.
• Our team and that vendor are using the same data files we produced for Phase 2 of the Proof-of-Concept project.

Our goal is to provide Knowledge Workers with a one-stop shop for Biomedical information and the means to analyze this information on an as-needed basis, i.e., the Knowledge Worker will be able to specify the sub universe of articles on which NLP algorithms are applied. The Blockchain platform with the embedded NLP will retrieve any configuration of articles and will generate the visualizations for the Text analysis with NLP.

Additional details are included in the following article:

2.0 LPBI is a Very Unique Organization

Author: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2021/03/02/2-0-lpbi-is-a-very-unique-organization/

PERSONAL PAGES OF INTERNS

All milestones are recorded on the Personal Pages

Madison Davis, Research Assistant 1 – PERSONAL PAGE on 2021 Medical Text Analysis

Danielle Smolyar, Research Assistant 3 – PERSONAL PAGE on 2021 Medical Text Analysis

Inbar Ofer, Research Assistant 3 – PERSONAL PAGE on 2021 Medical Text Analysis

Adina Hazan, PhD, PostDoc in Pharmaceutical Sciences, Medical Text Analysis with Machine Learning

Amandeep Kaur, BSc., MSc. (exp. 5/2021) – Research Associate 2, Medical Text Analysis and IT Infrastructure Python Coder

Premalata Pati, PhD, PostDoc in Pharmaceutical Sciences, Medical Text Analysis with Machine Learning

Zoom LINK for Meetings 

https://us02web.zoom.us/j/84036067511?pwd=Tlo3WGs5T0M0NDJSVEVqOW80cnpmQT09

LPBI Group will run THREE MAJOR INTERNSHIPS: Volunteer base

• We Offer esteemed Affiliation, Mentorship by Scientists
• NEW skills development in NLP, ML, AI applications to Medical Text and Drug Discovery
• References and Resume paragraph on accomplishments and goals during the INTERNSHIP
• Opportunity to contribute to Publications
• Explorations of opportunities in Life Sciences in the US

Three INTERNSHIPS in LIFE SCIENCES, Medicine, Biological Sciences, Drug Discovery

#1: Text Analysis [Medical] with Wolfram: Natural Language Processing with a NEW cohort of INTERNS and our Summer Interns that will choose to stay

• https://pharmaceuticalintelligence.com/2020-summer-internship/

#2: Synthetic Biology Software for Drug Design in Glycobiology for our Joint Venture with ABI-LAB, with Dr. Raphael Nir, PhD, President & CSO

#3:  Web Design and Marketing Communications – Journalism in Pharmaceutical MEDIA

• 2020/2021 LPBI Plan for IT Projects & Reseach Projects – LPBI’s TASKS for Research Assistants & Associates

UPDATED on 2/13/2021

Assignments for Interns updated on 2/13/2021

All the Intern will be using Madison’s code and workflow to generate all Steps of Visualization:

1. WordClouds
2. Bar Diagrams
3. Hyper-graphs
4. Tree Diagrams
5. Template for Interpretation to be filled up by domain knowledge expert
6. Present all in PowerPoint
7. Populate a Database with 1 to 5, above
8. Use DropBox for Proof-of-Concept and for all the Books NOW in DropBox

Series B: Frontiers in Genomics Research

Assigned intern: Madison Davis – Proof-of-Concept: 16 articles on Genomics, 12 articles in Cancer Biology & Therapies Research Category & Genomics Volume 2

• Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology

Assigned intern: Amandeep Kaur – Genomics Volume 1, Chapter 21: CRISPR & Chapters: 1-20 in Genomics Volume 1 

• Volume One: Genomics Orientations for Personalized Medicine

Series C: e-Books on Cancer & Oncology

Assigned intern: Danielle Smolyar – Proof-of-Concept: 16 articles on Cancer, 12 articles in Cancer, the Chapter of Warburg article by Dr. Larry and Cancer Volume 1,  2,400 pages – Chapters 1 to 6

• Volume One: Cancer Biology and Genomics for Disease Diagnosis

Assigned intern: Premalata Pati, PhD – Cancer Volume 1,  2,400 pages – Chapters  to 7 to 12

• Volume One: Cancer Biology and Genomics for Disease Diagnosis

Assigned intern: TBA – Cancer Volume 2, 3,400 pages

• to be shared with TBA Intern(s) or current intern reassigned after completion of their current assignments 

Series A: e-Books on Cardiovascular Diseases

Assigned intern: Adina Hazan, PhD – Proof-of-Concept: 13 articles on Calcium & CVD & e-Books on CVD

Series D: e-Books on BioMedicine – Metabolomics, Immunology, Infectious Diseases, Reproductive Genomic Endocrinology

Assigned interns: TBA

Series E: Patient-Centered Medicine – LINKS to e-Books & Cover Pages for Volumes 1,2,3,4

Assigned interns: TBA

UPDATED on 1/17/2021

Dear Madison,

I visited the google doc LINK on your Personal Page on 2021 Medical Text Analysis.

Please also Place the PowerPoint Presentation on the Google Doc AND please the LINK to it on your PERSONAL PAGE.

Madison Davis, Research Assistant 1 – PERSONAL PAGE on 2021 Medical Text Analysis

I am very proud of you to generate the Tree Diagram for the 16 articles in Genomics.

Please create a Tree Diagram one for each of the 16 articles.

• I assume that that will provide the words and the edges connected we need to submit to the Domain Knowledge Expert to write an interpretation for.

Please add all the new graphs into the PowerPoint and replace the existing Bar Graphs and Hyper-graphs without the legend

As you will generate 16 Tree diagrams we will compare the hyper-graph with the Tree Diagrams and decide WHICH is the way we go 

• Next, you need to rest a whole week from LPBI
• Next, we would like to get a Tree diagram for ONE article in the 16 Genomics articles and 6 articles in the main Research Category assigned to that ONE article
• Next, Madison goes to Genomics Volume 1 and looks at all the articles in CHAPTER 1 – ONE Tree Diagram for that article collection
• SEMANTIC ANALYSIS is expected to be the strongest among articles in one chapter in any book among our 18 volumes

• Volume One: Genomics Orientations for Personalized Medicine

For Scaling up Madison will work also on

• Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology

• Interpretation of our Domain Knowledge Expert of the Tree Diagram for ALL the articles in Genomics Volume 1, Chapter 1 – will be the one that will bring to completion the Proof-of-Concept for Genomics Contnet

THEN will be ready to call the meeting with the Insurer.

By early March 2021 – We need Madison to write a Summary report on

• What were the contributions that this internship did you your professional development in the first 6 months – 8/15/2020 – 2/28/2021
• What are the NEW skills you developed in conjunction with working on the Proof-of-Concept

Dear Danielle, 

• ALL of the ABOVE – we need be done by Danielle on Cancer Content.
• You need all articles from CHAPTER 1 in CANCER Volume 1

• Volume One: Cancer Biology and Genomics for Disease Diagnosis

By early March 2021 – We need Danielle to write a Summary report on

• What were the contributions that this internship did you your professional development in the first 6 months – 8/15/2020 – 2/28/2021
• What are the NEW skills you developed in conjunction with working on the Proof-of-Concept

I am very pleased that the progress to date enables me to see the forthcoming COMPLETION of the Proof-of-Concept nearing for Genomics and for Cancer.

Dear Dr. Williams,

• Please ready yourself for several Tree Diagrams interpretations in Genomics and in Cancer
• Please EXPLORE HOW can we start another Gallery on WordPress.com for ALL THE IMAGES GENERATED BY 2.0 LPBI
• Shall we date them 2021 upon Upload by the Creator of the graph? 
• Then we know they are 2.0 LPBI IP vs 
• Images uploaded in 2012-2020 which are the 5,100 images, aka 1.0 LPBI IP 

Please ALL – read Madison’s e-mail, below.

THANK YOU

Best regards,

Aviva

Aviva Lev-Ari, PhD, RN

Director & Founder

https://lnkd.in/eEyn69r

From: Madison Davis <madisond2302@gmail.com>

Date: Sunday, January 17, 2021 at 3:16 PM

To: “Aviva Lev-Ari, PhD, RN” <aviva.lev-ari@comcast.net>

Subject: Re: Submitted – See attachment

Hi Aviva,

I made an updated, comprehensive instructions guide, and it has been posted on the 2021 Text Analysis Website.  Danielle and I have updated our personal pages showcasing our code and graphics.

I’ve included in these diagrams and documents Tree Diagrams by Wolfram.  Tree Diagrams are actually fairly similar to Hyper-graphs, and they are visually appealing.  I made an algorithm to showcase all Tree Diagrams for all 16 articles, and I will attach a photo here:

Thanks,

Madison Davis

On Sat, Jan 16, 2021 at 9:45 PM Aviva Lev-Ari <aviva.lev-ari@comcast.net> wrote:

Dear Madison,

I was happy to write for you the recommendation. I wish you best of luck to get into the RSI summer program.

Got word Robin that she will conduct a National search to find interns for LPBI.

We wish to have one or more interns on each volume, we got 18 volumes.

All the Intern will be using your code and work flow to generate:

1. WordClouds
2. Bar Diagrams
3. Hyper-graphs
4. Template for Interpretation to be filled up by domain knowledge expert
5. Present all in PowerPoint
6. Populate a Database  with 1 to 4, above

I suggest that you will post all the instructions on 2021 Medical Text Analysis Portal

The code you wrote you will place on your Personal Page on the Portal

• Danielle is following your work on Genomics articles on her assigned 16 Cancer articles

• Adina is starting the Proof-of-Concept on 13 Cardiovascular articles. We have 6 volumes on heart diseases. She will connect you for instructions

• Amanda is starting a Proof-of-Concept for Chapter 21: CRISPR in Genomics Volume 1 – all articles in this chapter.

She will expand to all articles in the several Research Categories on CRISPR in the ontology of the Journal

• Inbar will start in 6/2021 a Proof-of-Concept on Series D, she will choose her first volume

All new Interns, each will have a volume,

We are building a Team of 18 interns

Regarding of the good new you have for LPBI:

• These are beautiful results, in attachment.

We will have a bar diagram for each of the 16 articles.

Please explore “Tree Diagram” and figure out if Wolfram allows to represent the hyper-graph as a Tree Diagram

I would like to suggest to run a hyper-graph and a Tree diagram for one article at a time

We will choose among the two only one after deliberation among the two produced for few articles to become the Standard for 3., above: Hyper-graph

The vectors within one article will be provided for semantic interpretation by the domain knowledge expert.

Try above suggestions and let’s look at the results.

Ask me questions as you feel needed.

Aviva Lev-Ari, PhD, RN

Founder & Director

Leaders of Pharmaceutical Business Intelligence (LPBI) Group, Boston

PharmaceuticalIntelligence.com

AvivaLev-Ari@alum.berkeley.edu

617-755-0451

Twitter: @pharma_BI @AVIVA1950

Profile on LinkedIn

Begin forwarded message:

From: Madison Davis <madisond2302@gmail.com>

Date: January 16, 2021 at 9:46:43 PM EST

To: Aviva Lev-Ari <aviva.lev-ari@comcast.net>

Subject: Re: Submitted – See attachment

To Aviva,

I just want to thank you so much for writing a letter of recommendation for me!  It means a lot to me, and I truly appreciate it.

Good news for the LPBI 2.0 Project: I’ve been able to come up with some automation processes so that the word frequencies can be done for any number of articles now, and the hypergraphs now show connections over all 16 articles.  I will attach some photos and notify Danielle about editing the Cancer documents.

Best,

Madison Davis

UPDATED on 1/16/2021

Instructions for launching a Proof-of-Concept in one of the following five domains:

SEE UPDATE on 2/13/2021, above

• Series A: e-Books on Cardiovascular Diseases

Assigned intern: Adina Hazan – Proof-of-Concept: 13 articles on Calcium & CVD & e-Books on CVD

• Series B: Frontiers in Genomics Research

Assigned intern: Madison Davis – Proof-of-Concept: 16 articles on Genomics & Genomics Volume 2

Assigned intern: Amandeep Kaur – Genomics Volume 1, Chapter 21: CRISPR & Genomics Volume 1 to be also shared with Madison Davis

• Series C: e-Books on Cancer & Oncology

Assigned intern: Danielle Smolyar – Cancer Volume 1 to be shared with other Intern(s) – 2,400 pages

Assigned intern: TBA – Cancer Volume 2 to be shared with other Intern(s) – 3,400 pages

• Series D: e-Books on BioMedicine – Metabolomics, Immunology, Infectious Diseases, Reproductive Genomic Endocrinology

Assigned interns: TBA

• Series E: Patient-Centered Medicine – LINKS to e-Books & Cover Pages for Volumes 1,2,3,4

Assigned interns: TBA

Steps in the development of a Proof-of-Concept

for one of the five e-Series: A, B, C, D, E

Create a PowerPoint file like this attachment, you will need to get Text been analyzed by NLP 

STEPS in Data Preparation

1. Create an MS Word file for each of the X articles
2. Create file X+1 that is ALL of the files into one 
3. Get from Madison and Danielle HOW they did WordClouds using Wolfram
4. For WordItOut.com use same criteria as they used a slide in the attachment presents that
5. Create Bar Chart one per article AFTER you eliminate words as The, an, a, and, 
6. Hyper-graph creation – use code written by Madison
7. Communicate with your Domain Knowledge Expert for Interpretation of the NLP results in the format of hyper-graph

UPDATED on 8/20/2020

From: Aviva Lev-Ari <aviva.lev-ari@comcast.net>

Date: Thursday, August 20, 2020 at 6:39 AM

To: Madison Davis <madisond2302@gmail.com>

Cc: “Stephen Williams, PhD” <sjwilliamspa@comcast.net>, “Ofer Markman, PhD” <oferm2020@gmail.com>, “Irina Robu, PhD” <irina.stefania@gmail.com>

Subject: Re: Internship Progress

Very impressive.

Let me know 

1. When I can edit your first post

2. What do you suspect could have been behind the Microsoft Decline decision

3. I highly appreciate that fact that you reapply !!!

Note: when our Summer Intern Daniel had applied to a Developer Account for Twitter.com to use Tweepy and Pyton, we had three exchanges with Twitter Team till we were approved a Developer Account.

4. Uploading the Text into container is Step 1.

The next step would be to activate the NLP algorithm on the Text and generate Hypergraphs and other output that the NLP program generate

5. We need to understand Microsoft NLP algorithm, I.e., is driven by frequency of words or by a correlation matrix of inverse distances or my semantics logic predicates

6. Example:

23andMe – sequence a Genome of one Person at a time

6.1 it used algorithm x for sequencing (Illumina)

6.2 It compares it to a benchmark

6.3 It issue a report that has

6.3.1 text 

6.3.2 Geographic Map of ancestry

6.3.3 Graphics on genes

6.3.4 List of genes over expressed posing Risk for Diseases x, y, z and protection again Disease k, l, m

I assume that AZURE API for NLP algorithms when apply on text for FHRI Service will yield a report like 6.3, above.

Such a report will be interpreted by LPBI experts.

It will be very nice if you would create the following:

GENOMICS:

16 articles

For each article:

1. Create a MS Word Text file (no figures)

2. Place figures in another file assigned the articleID images removed from

3. Repeat 1 & 2, above for all 16 articles

Top 12 viewed articles:

4. Perform 1,2,3 above for each of the 12 – Expect for Our Team, this, N= 11

Create Two containers:

• One for Genomics

• One for Top Viewed articles

• One for Cancer – Danielle will perform 1,2,3, above for 16 articles on Cancer, you will write a Standard Operation Procedure for HOW to perform 1,23, above for any collection of articles from the Journal. For each article we need to have one column of Categories of Research that any article had been assigned to by the Author, that list is in the Table of the Collection of 16 articles in Genomics, Cancer and Top Viewed articles.

5. We need a DESCRIPTION File for AZURE’s NLP algorithm

6. We need for 5, above same information as 6.3, above.

A DESCRIPTION File about the output of AZURE’s NLP algorithm

Please ask questions 

It is OK to contact AZURE Customer Service and discuss what is your goal and get a Microsoft representative to walk you through the steps to follow to achieve the OUTPUT of application of NLP to our Article’s Text.

• Daniel, mentioned, above had contacted WordPress.com to clarify if a count of Views of our Home Page include or not click done from the Dashboard of an LPBI team member vs a count of a view does not include Internal vs External IP Address of Website Access.

•• That clarification involved 6 e-mail exchanges between Daniel and WordPress.com (WP) representative.

••• that exchange is included in the LPBI Documentation Appendix as evidence for WP definition of a “View” of an article on our Site

•••• Any Click on an Article is assign the intent to download and agreement to pay $30. 

••••• Any Click on the Homepage is assign the intent to access for a Search of a Private Archive and agreement to pay $5.

We derive the Valuation of the Journal based on # of Views of each article across 6,000 articles and across 687,000 searches on the Homepage times the two price categories above for 1.8 Million for both. The Cumulative projection to 2025 is of $48 Million.

The ONE GRAPH I sent last evening.

I mention the WP e-mail exchange to encourage you to contact an AZURE representative to get your guidance on the process and maintain full documentation which we will in due time VOPY and PASTE as the instructions apply to achieve the 6.3, above LIKE a report for our TEXT ANALYSIS operation.

Any questions, please e-mail me or coordinate availability for Zoom meeting with and any other Mentor at LPBI.

A. I am aware about School year start.

B. As you mentioned, time management will allow you to pursue that Annual Internship which will develop your 

1. experience on technical domains and on 

2. corporate/enterprise environment 

I am very pleased to watch you grow and excel with our Team.

BACKGROUND

2020 VISION 

https://pharmaceuticalintelligence.com/vision/

2020 VISTA 

https://pharmaceuticalintelligence.com/2019-vista/

BioMed e-Series 

https://pharmaceuticalintelligence.com/biomed-e-books/

Artificial Intelligence in Cancer & Genomics Portal 

https://pharmaceuticalintelligence.com/ai-in-genomics-cancer/

2020 Summer Internship on Data Curation & Data Annotation 

https://pharmaceuticalintelligence.com/2020-summer-internship/

Testimonials 

https://pharmaceuticalintelligence.com/praising-lpbi/

Founder 

https://pharmaceuticalintelligence.com/founder/

Research Assistants 

https://pharmaceuticalintelligence.com/contributors-biographies/research-assistants/

Overarching Plan: 9/2020 – 9/2021

 The Overarching Plan will be updated with a Date and will GUIDE all INTERNS activities

The New Strategies: TNS #1, #2, #3, #4, #5, #6

TNS #1: TEXT Analysis on our CONTENTS: NLP, ML, AI – INSIGHTS MEAN VALUE and Up-selling content = NEW WARES to be brought to the market

Phase 1: Natural Language Processing(NLP) – 24 months FREE Microsoft AZURE for Health

• Text Analysis done in parallel on three LPBI’s Article Collections building a Proof of Concept performed by LPBI Group’s 2020/2021 Academic Internship in Medical Text Analysis (MTA) with Natural Language Processing (MTA-NLP):
• 9/2020 – 9/2021 – Academic INTERNSHIPS in LIFE SCIENCES, Medicine, Biological Sciences, Drug Discovery 
• Inputs for Proof of Concept are the following three:

(1) Top 12 articles by views (all domains)

(2) Sixteen Cancer Articles representing 8 topics in Cancer Volume 1

(3) Sixteen Genomics Articles representing 21 chapters in Genomics Volume 1

Phase 2: Piloting the Proof of Concept on 4 of LPBI BioMed 16 volumes:

Cancer, Volume 1 & 2 and Genomics, Volume 1 & 2

• Expand applications of Microsoft AZURE and EXPERIMENT with Text Analysis The Wolfram Language
• Comparison of NLP results obtained for Microsoft AZURE and EXPERIMENT with Text Analysis The Wolfram Language
• Application on the ingress TEXT from:

Series C: e-Books on Cancer & Oncology

Volume 1:

Cancer Biology and Genomics for Disease Diagnosis

http://www.amazon.com/dp/B013RVYR2K 

Volume 2:

Cancer Therapies: Metabolic, Genomics, Interventional, Immunotherapy and Nanotechnology in Therapy Delivery

http://www.amazon.com/dp/B071VQ6YYK 

and

Series B: Frontiers in Genomics Research

Volume 1: 

Genomics Orientations for Personalized Medicine

http://www.amazon.com/dp/B018DHBUO6

Volume 2:

Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS & BioInformatics, Simulations and the Genome Ontology

https://www.amazon.com/dp/B08385KF87

Phase 3: Scaling up NLP, ML, AI to LPBI Group’s FOUR Corpuses Using LPBI’s Vendor of Choice:

• The Wolfram Solution for Biological Sciences
• The Wolfram Data Drop is an open service that makes it easy to accumulate data of any kind, from anywhere—setting it up for immediate computation, visualization, analysis, querying, or other operations

LPBI Group’s FOUR Corpuses

(1) All 6,000 Journal Articles 

(2) 16 Books in Medicine 

(3) 60 e-Proceedings & 36 Tweet Collections of TOP Global Medical and Biotech Conferences, 2013 – 2020

(4) Content Segmentation by other criteria for Narrow casting the content of the journal ontology, Categories of Research (N = 715). About 70% are related to Drug DIscovery

More Instructions

1. The 2020 Summer Internship YIELDED the following three Deliverables which will serve as INPUT for the PROOF OF CONCEPT that the INTERNS in LPBI Group’s 2020/2021 Academic Internship in Medical Text Analysis with Natural Language Processing (MTA-NLP) will be using
2. GOAL for 2020 4Q: TASK #1
   Launch and Completion of the Proof of Concept – and its presentation to a TOP HealthCate Insurer in UT and to a Healthcare Blockchain Transaction Network
3. TASK #2: 2021 – GOAL: Upon completion of the Proof of Concept —>>>> We will scale up the MTA-NLP operation to our following 4 Volumes: (a) Cancer: Volumes 1 & 2 and (b) Genomics: Volumes 1 & 2 – – See Overarching PLAN, above for updates
4. TASK #3: Upon completion of TASK #2, we will engage in task expansion and Scaling up NLP, ML, AI to LPBI Group’s FOUR Corpuses: – See Overarching PLAN, above for updates

(1) All 6,000 Journal Articles 

(2) 16 Books in Medicine 

(3) 60 e-Proceedings & 36 Tweet Collections of TOP Global Medical and Biotech Conferences, 2013 – 2020

(4) Content Segmentation by other criteria for Narrow casting the content of the journal ontology, Categories of Research (N = 715). About 70% are related to Drug DIscovery

• DELIVERABLES produced by INTERNS during LPBI Group’s 2020 Summer Internship on Data Curation & Data Annotation SERVE AS INPUT for

  2020/2021 Academic Internship in

  Medical Text Analysis (MTA)

  with

  Natural Language Processing (MTA-NLP)

TASK #1:

USE ONE of the Three following INPUTS to be used in building the Proof of Concept described in

https://pharmaceuticalintelligence.com/2021-medical-text-analysis-nlp/

Three INPUTS to be used in building the Proof of Concept

WordCloud Visualization of LPBI’s Top Twelve Articles by Views at All Time and their Research Categories in the Ontology of PharmaceuticalIntelligence.com

Curators: Daniel Menzin, Noam Steiner-Tomer, Zach Day, Ofer Markman, PhD, Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2020/07/21/wordcloud-visualization-of-lpbis-top-twelve-articles-by-views-at-all-time-and-their-research-categories-in-the-ontology-of-pharmaceuticalintelligence-com/

 

WordCloud Visualization of LPBI’s Top Sixteen Articles on CANCER in eight categories and by Views at All Time and their Research Categories in the Ontology of PharmaceuticalIntelligence.com

Curator: Stephen J. Williams, PhD and WordCloud Producers: Daniel Menzin, Noam Steiner-Tomer, Zach Day, Ofer Markman, PhD and Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2020/07/30/wordcloud-visualization-of-lpbis-top-sixteen-articles-on-cancer-in-eight-categories-and-by-views-at-all-time-and-their-research-categories-in-the-ontology-of-pharmaceuticalintelligence-com/

 

WordCloud Visualization of LPBI’s Top Sixteen Articles on GENOMICS by Views at All Time and their Research Categories in the Ontology of PharmaceuticalIntelligence.com

Curators: Stephen J. Williams, Aviva Lev-Ari, PhD, RN and WordCloud Producers: Daniel Menzin, Noam Steiner-Tomer, Zach Day, Ofer Markman, PhD

https://pharmaceuticalintelligence.com/2020/07/30/wordcloud-visualization-of-lpbis-top-sixteen-articles-on-genomics-by-views-at-all-time-and-their-research-categories-in-the-ontology-of-pharmaceuticalintelligence-com/

TASK #2:

Expand applications of Microsoft AZURE to – See Overarching PLAN, above for updates

Series C: e-Books on Cancer & Oncology

Volume 1:

Cancer Biology and Genomics for Disease Diagnosis

http://www.amazon.com/dp/B013RVYR2K 

Volume 2:

Cancer Therapies: Metabolic, Genomics, Interventional, Immunotherapy and Nanotechnology in Therapy Delivery

http://www.amazon.com/dp/B071VQ6YYK 

and

Series B: Frontiers in Genomics Research

Volume 1: 

Genomics Orientations for Personalized Medicine

http://www.amazon.com/dp/B018DHBUO6

Volume 2:

Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS & BioInformatics, Simulations and the Genome Ontology

https://www.amazon.com/dp/B08385KF87

PERSONAL PAGES OF INTERNS

Madison Davis, Research Assistant 1 – PERSONAL PAGE on 2021 Medical Text Analysis

Danielle Smolyar, Research Assistant 3 – PERSONAL PAGE on 2021 Medical Text Analysis

Inbar Ofer, Research Assistant 3 – PERSONAL PAGE on 2021 Medical Text Analysis

Adina Hazan, PhD, PostDoc in Pharmaceutical Sciences, Medical Text Analysis with Machine Learning

Amandeep Kaur, BSc., MSc. (exp. 5/2021) – Research Associate 2, Medical Text Analysis and IT Infrastructure Python Coder

This page has the following sub pages.

• Madison Davis, Research Assistant 1 – PERSONAL PAGE on 2021 Medical Text Analysis
• Danielle Smolyar, PERSONAL PAGE on 2021 Medical Text Analysis
• Inbar Ofer, Research Assistant 3 – PERSONAL PAGE on 2021 Medical Text Analysis
• Adina Hazan, PhD, PostDoc in Pharmaceutical Sciences, Medical Text Analysis with Machine Learning
• Amandeep Kaur, BSc., MSc. (exp. 5/2021) – Research Associate 2, Medical Text Analysis and IT Infrastructure Python Coder
• Premalata Pati, PhD, PostDoc in Biological Sciences, Medical Text Analysis with Machine Learning