COVID-19 and AI: A Virtual Conference – Human-Centered Artificial Intelligence, Stanford University, 4/1/2020, 9AM PST – 3:30PM PST | Leaders in Pharmaceutical Business Intelligence (LPBI) Group

Wednesday, April 1, 2020

*Speakers and session titles are subject to change

*All times are in PDT

Time	Session Information
9:00-9:20	Welcome and Preview John Etchemendy, Denning Family Co-Director, Stanford Institute for Human-Centered Artificial Intelligence; Provost Emeritus, and Patrick Suppes Family Professor in the School of Humanities and Sciences, Stanford University Fei-Fei Li, Denning Family Co-Director, Stanford Institute for Human-Centered Artificial Intelligence; Sequoia Professor of Computer Science, Stanford University Russ Altman, Kenneth Fong Professor and Professor of Bioengineering, of Genetics, of Medicine (General Medical Discipline), of Biomedical Data Science, and, by courtesy, of Computer Science, Stanford University; Associate Director, Stanford Institute for Human-Centered Artificial Intelligence Michele Elam, William Robertson Coe Professor of Humanities Department of English Center for Comparative Studies in Race & Ethnicity, Stanford University; Associate Director, Stanford Institute for Human-Centered Artificial Intelligence Rob Reich, Professor of Political Science, Stanford University; Associate Director, Stanford Institute for Human-Centered Artificial Intelligence
9:20-10:30	Session I: Landscape and Framing Talk Titles & Speakers Challenges Responding to COVID-19: Perspectives from a Physician and Policy Maker Congressman Ami Bera, California’s 7th Congressional District in the U.S. House of Representatives past pandemics: SARS, MERS, EBOLA, ZIKA – preparedness during Obama, disband 12/2018, 11/2019 and 1/2020 reports from China on COVID-19 came along,U.S. House of Representatives 2/2020 – Ban of Travel to China, preparedness was needed, UC, Davis at the front CDC pushing own test cause lost of time – changing criteria social distancing Sacramento County – Hospitals prepared and ramped up testing FL and TX are lagging on ramped up testing and social distancing policy Big data and AI in congress – as next steps Korea, Singapore, China – Serological testing represent diffusion in the community and immunity in communities vs Diagnostics Testing (virus present or no) John Hopkins Data Source – North hemisphere vs South hemisphere An Academic Medical Center’s Data Science Response to a Pandemic Nigam Shah, Associate Professor of Medicine (Biomedical Informatics) and of Biomedical Data Science, Stanford University Operational Planning – Utilization – Resource planning Clinical – who to test Research Questions – ACE2 receptors Epidemic simulations – when get out from lockdown Next five Days – Predictions for 5 days using simulations: Growth rate & Disease burden County like ONE huge hospital – rolled up to Regions Relations from Social distancing and Hospital planning Population studies: Geography information in Santa Clara county – Stanford Covid-19 Report Administration to legally command Hotels and Companies to retool change temporary sovereignty Issues in Responsible Reporting of COVID-19 Seema Yasmin, Director, Stanford Health Communication Initiative; Clinical Assistant Professor, Medicine, Primary Care and Population Health, Stanford University Epidemic Intelligence Service Officer (Public Health Physician & Journalist on Pandemics and Epidemics March 7, 2020 Italy news quarantine of 16 million lockdown large movement of people moving out of lockeddown areas, this movement based on information lead to spread of the viral spread Hold information, report truth vs false epidemic tool kit for Reporters Global Best Practices in Controlling the COVID-19 Pandemic Michele Barry, Professor, Senior Associate Dean, Global Health, Director, Center for Innovation in Global Health; Medicine & Senior Fellow, Woods Institute and at the Freeman Spogli Institute, Stanford University 5Million people travel out of Huhan Singapore – Free testing 1st country Temp testing stay at home, text phone from Authorities, show picture they are in quarantine for 5 days even if negative – unified Government reporting, Daily messaging, chronicals, social responsibility TRACE together – Bluetooth tool on distance among people – Information on quarantine – no lockdown CHINA – contact racing surveillance scanning temperature, strict social distancing IRAN – religious interference at later date Hong Kong – tracing bracelets for tracing quarantine Street locations of infected individuals no identity USA – Lack of Testing, State responsibility, CDC nor allowed in a State if not invited Evidence based intervention with AI Masks instructions in the US different than the World: Paper mask vs cloth mask. Airborn infection will be mitigated by Masks of any materials not only paper – people can make to create OWN MADE masks CHINA – Infection avoidance in Healthcare workers: Googles, Mask, Eye shields – lower infection of Health care workers Panel Discussion and Audience Q&A Moderator: Rob Reich
10:40-11:40	Session II: Social Impacts & Bio-Security Talk Titles & Speakers COVID-19 Infodemic and Crisis Informatics Kate Starbird, Associate Professor, Human Centered Design & Engineering, University of Washington Human responses to crisis anxiety and unknown quarantine – collective sense making rumors absence of information to make decisions over abandance of information trustworthy vs misinformation vs disinformation vulnerability to information searching seeking and sharing crisis communicators: Trust in Official sources, use science for recommendations Agencies risk loosing trust Politician diminish trust by avoiding truth Social Media took action to avoid misinformation vs disinformation going viral Platforms take actions more at Present than in the Past due to lessons on misinformations stifling and censoring are context dependent misinformation vs disinformation Blames someone else like the US COVID-19: Misinformation & Disinformation Renée DiResta, Technical Research Manager, Stanford Internet Observatory China’s English channels State sponsored narrative build Propaganda and control information China White Information ecosystems channels – Attributable diplomats in the English language Google bans China China’s Informational Properties on Google Significant audience on Google by China’s Informational Properties China’s Informational Properties on Google Ads – need to manage perception of China related to narrative COVID-19 Pandemic January 2020, US is one month behind – representation of positive CHina due to response effectiveness vs the government of US positive handling of Infections in babies Doctor discover was arrested was infected and DIED. China’s report was of a HERO doctor not mentioning his detention Removal from SEO causes deemphasizing CDC and WHO – recognitions of institutions as authorities COVID-19 & Biosecurity Megan Palmer, Senior Research Scholar, Stanford Center for International Security and Cooperation, Stanford University evolving Security and Cooperation coordination defense Pandemic consequences under estimated Labs causing accidents Avoiding over indexing an event technology for Good vs Ill: AI and Vaccine vs devastating events by viruses Novel viruses in Labs constructed by gene engineering in Switzerland lab posted on the Internet to develop vaccine – use can be negative – reconstruction of pathogens Methods social psychology, gov.t strategy to new AI used in Attribution Infrastructure: Privacy, Sharing, security, surveillance psychology of risk “Foreign Bodies”: COVID-19 and Xenophobia Eram Alam, Assistant Professor, History of Medicine, Harvard University “Chinese Virus” Xenophobia 1/27/2020 – 138 years apart 1882 – Chinese body perceived in Trade war between nations in adversarial relations related to security body can be host victim by invading vectors Social distance defined and redefined Archival work and AI Surveillance has material consequences, scientific good Diet of Chinese including eating wild animals stigmatized – social distancing vs Europe and US Travel foreignness of the viral becomes foreignness of the foreign body Panel Discussion and Audience Q&A Moderator: Rob Reich Will the coronavirus pandemic change societies for the generations to come
11:50-1:30	Session III: Tracking the Epidemic Talk Titles & Speakers Taiwan’s Use of Data Analytics to Control COVID-19 Jason Wang, Director, Center for Policy, Outcomes and Prevention, Stanford University; Associate Professor of Pediatrics, The Lucile Salter Packard Children’s Hospital and of Medicine Since 2003 Taiwan is preparing for a Pangemic, JAMA paper on the topic is beebn reported Location of patient Taiwan – National Epidemic Center 100 persons 24×7 in the Command Center Taiwan activated the commend center in December 2019 All flight entering the country – Level 3 alert country: China Huhan, Hubei, another Chinese city Quarantine all arriving from Level 3 alert country National STOKE PILES Activated – production of masks from 2K to 11K per day Logistics, articulate, agile, Tools for Estimating Unreported Infections of COVID-19 Lucy Li, Infectious Data Scientist, Chan Zuckerberg Biohub Undetected infection using viral genome sequencing DIagnostics testing Methods for Real Time Mapping of COVID-19 Cases Worldwide John Brownstein, Professor, Department of Pediatrics, Harvard Medical School Late December 2019 collecting dat a HealthMap – public domain Baidu – has movement information connected with cases Temperature Data published Buoy data base customized to collect MA data on Temperature community mapping data for Health policies with epidemiological data Epidemiological Forecasting Tools for COVID-19 Ryan Tibshirani, Associate Professor, Department of Statistics and Machine Learning Department, Carnegie Mellon University CDC Forecasting Influenza – National and State level data captured is from Physicians – is one week old Forecast next week Hospitalization predicted Worse case scenario Mechanistic pf the disease differential equation Statistical models are not available DISTRIBUTION SHIFT – represent the prediction of a pandemic Efforts from Influenza used for coronavirus FOrecast distribution not cases or individuals A Mobile App Intervention to Slow COVID-19 Using Crowdsourced Data Tina White, Ph.D. Candidate, Department of Mechanical Engineering, Stanford University China death toll >1000 China launched App to monitor quarantine early 1/2020 GPS based new App for contact tracing – regulation on data from GPS AI for COVID-19: An Online Virtual Care Approach Xavier Amatriain, CoFounder and CTO, Curai Lack accessibility to health care systems HC Accessibility and Scalability AI based HC IT System PDA – Personalized Diagnostics Assessment – for self reporting AI Automations + Physicians + embed home testing _ Patients symptoms BERT Language modelnavigate long questionnaire ML + Expert system to create simulated cases to create a DIAGNOSTICS COVID-19 model Knowledge Technology to Accelerate Open Science in Addressing the COVID-19 Pandemic Mark Musen, Professor, Department of Medicine (Biomedical Informatics) and of Biomedical Data Science, Stanford University Output of Science and of Data is shared for discoveries by all scientists Data available without a catalogue – no Meta data Data interoperable, reusable, Meta data: GEO at NIH find a specimen NCBI BIOSample – data cleanup needed FAIR Data on COVID-19 – CEDAR – Classes of experiments FORM/Template of data types at CEDAR at Stanford VODAN – CEDAR Data infrastructure VODAN – Viral Ouput Data Network What We Can Learn From Twitter Analysis About COVID-19 Johannes Eichstaedt, Assistant Professor (Research), Department of Psychology, Stanford University; HAI Junior Fellow Unemployment and life satisfaction Twitter analysis of Clusters of Tweets: Urban Areas: Buying panic Educated counties AGE – Voting Mental illness of loneliness – COVID-19 Adjustment Panel Discussion and Audience Q&A Moderator: Russ Altman
1:45- 3:00	Session IV: Treatments & Vaccines Talk Titles & Speakers Rapid Analysis of SARS-CoV-2 Genomic Content Using the Functional Genomics Platform Kristen Beck, Lead Bioinformatician, AI and Cognitive Software, IBM Functional Genomics Platform – in a RDB at IBM COVID-19 Genes, proteins of +200 viruses for comparative analysis Building AI by Training on Variants for anti-viral interactions SNAPS COVID-19 Machine Learning Challenges Anthony Goldbloom, Founder and CEO, Kaggle Three channels @Kaggle NLP Challenge – Coronavirus – all articles subjected to NLP key questions – Automated literature review Forecast cases and fatalities by Cities and Counties by Latitute and Longitude: Different pattern among the entities Data set curation models Machine Learning Enabled Systems for Delivering Care to Critically Ill Patients Ron Li, Clinical Assistant Professor of Medicine, Hospital Medicine and Biomedical Informatics, Stanford University AI used to deliver care to cCOVID19 patients Interdependencies in care delivery using complex systems Understanding the process: Managment Patients with COVID19 – Hospital to ICU intupation caused arosol that endanger Providers – workflow design and clinical data updates the model ML Model validation and usefulness of the model RATE of CHANGE trigger intervention workflow AI-Assisted Elderly Care for Acute Infection and Chronic Disease Fei-Fei Li, Denning Family Co-Director, Stanford Institute for Human-Centered Artificial Intelligence; Sequoia Professor of Computer Science, Stanford University AGE Fatality rate and infection rate of the aged Interaction between Acute Infection and Chronic Disease Safety of home – AI sensors at home Sensors data on secure systems clinically data recognized from detection Fever detection – Thermo sensor for detection Mobility – infection behavior Sleep – patterns Diet – fluid intake and pill consumption SMART SENSORS Identifying COVID-19 Vaccine Candidates with ML Binbin Chen, MD and Ph.D. Student, Department of Genetics, Stanford University Immunogenic component of vaccine for COVID-19 spike protein bind epitome Repurposing Existing Drugs to Fight COVID-19 Stefano Rensi, Research Engineer, Bioengineering Department, Stanford University NLP – Mine the literature for Proteins: Genomes, genes, proteins Biophysics – docking simulations for the energy of 18 molecules as inhibitors Selection of candidate Panel Discussion and Audience Q&A Moderator: Russ Altman
3:00- 3:15	Wrap Up Russ Altman Rob Reich