What can machine learning offer to COVID-19 researchers?

SF Bay ACM Chapter
SF Bay ACM Chapter
Public group

Online event

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Details

By Rajiv Bhatia, MD, MPH, Stanford University

The event is jointly organized by ValleyML and SF Bay ACM.

7:00 Announcements, Chapter Election and Presentation

ZOOM link: For SFBay ACM members only. If you have not received the invitation, but wish to joint online before the meeting time, please click http://www.sfbayacm.org/join-us/ and send your receipt to Bill to vote for our new executive council.

Youtube live stream: https://youtu.be/JEpV9T8jM1E

Before the event, please contribute your perspectives by taking the 12 multiple choice Covid-19 Open Questions Survey using group number[masked]https://docs.google.com/forms/d/e/1FAIpQLSch_XdCZVms4VN-eMgBBIMHfTKO9bxrLNM8jqsC0SAcX6v2xA/viewform
More about the Project:
http://www.thecivicengine.org/coviduncertainties.html

Current Situation

●A novel virus, Covid-19, known to cause severe pneumonia and death, but with highly uncertain information on transmission behavior, human susceptibility, and immunity.
●Protective human behavioral and governmental responses driven by uncertainty and threat resulting in unprecedented economic disruption and unemployment.
●Secondary social and health harms including anxiety, delayed medical care, domestic violence, etc.
●Long term risks of maladaptive human behaviors, including economic depression, worsening social division and inequality.

Machine learning might ….

●Better understand or predict viral behavior both naturally and under different scenarios of control (e.g. disease modeling).
●Create an early warning indicator for hospital demand.
●Estimate real-time, location, specific individualized risks of Covid-19 disease at the individual, community, and business levels in real time. For example, what’s my risk of going to a restaurant in San Francisco tonight or taking a vacation to New York City.
●Sense where knowledge is converging and where uncertainty remains.
●Identify unexpected consequences, e.g. 3rd and 4th order effects, blind spots.

Speaker Bio

Dr. Rajiv Bhatia is a physician and internationally recognized health systems innovator. From 1998 through 2013, he led San Francisco's pioneering work on health impact assessment (HIA), community health indicators, and open civic data — all strategies to generate actionable civic intelligence on the health externalities of social and economic systems beyond healthcare. He currently works as a practicing primary care physician and as a consultant to civil society organizations, healthcare systems, and governments designing and implementing informatics practices to address the community, economic, and environmental roots of health.
[masked]
https://www.linkedin.com/in/rajivbhatia64

Some Reading

The Pandemic Doesn't Have to Be This Confusing https://t.co/4N687Gm5IH
Projecting the transmission dynamics of SARS-CoV-2 through the post pandemic period https://t.co/RR8kAH5BJ7
COVIDView Weekly Summary https://bit.ly/2ViFflZ
Hospitalization Rates and Characteristics of Patients Hospitalized with Laboratory-Confirmed Coronavirus Disease 2019 https://www.cdc.gov/mmwr/volumes/69/wr/mm6915e3.htm
Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV-2) https://science.sciencemag.org/content/368/6490/489
COVID-induced economic uncertainty and its consequences | VOX, CEPR Policy Portal https://voxeu.org/article/covid-induced-economic-uncertainty-and-its-consequences
My Health Today, Or Your Health Tomorrow - Rajiv Bhatia, MD https://medium.com/@rajivbhatia/my-health-today-or-your-health-tomorrow-3d9948135d49
If the world fails to protect the economy, COVID-19 will damage health not just now but also in the future https://t.co/RgM1xfAQ2q
Unexpected Scientific Insights into COVID-19 From AI Machine Learning Tool https://t.co/FtYaTKY7Ny
More readings please see the comment section.