MIT COVID-19 Datathon: data without boundaries

Eva M Luo; Sarah Newman; Maelys Amat; Marie-Laure Charpignon; Erin R Duralde; Shrey Jain; Aaron R Kaufman; Igor Korolev; Yuan Lai; Barbara D Lam; Megan Lipcsey; Alfonso Martinez; Oren J Mechanic; Jack Mlabasati; Liam G McCoy; Freddy T Nguyen; Matthew Samuel; Eric Yang; Leo Anthony Celi

doi:10.1136/bmjinnov-2020-000492

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Letter

MIT COVID-19 Datathon: data without boundaries

Authors

Eva M Luo Harvard Medical Faculty Physicians at Beth Israel Deaconess Medical Center Inc, Boston, Massachusetts, USA OB/GYN, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA PubMed articles Google scholar articles
Sarah Newman metaLAB, Berkman Klein Center, Harvard University, Cambridge, Massachusetts, USA PubMed articles Google scholar articles
Maelys Amat Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA PubMed articles Google scholar articles
Marie-Laure Charpignon Institute for Data, Systems, and Society, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA PubMed articles Google scholar articles
Erin R Duralde Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA PubMed articles Google scholar articles
Shrey Jain Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada PubMed articles Google scholar articles
Aaron R Kaufman New York University—Abu Dhabi Campus, Abu Dhabi, UAE PubMed articles Google scholar articles
Igor Korolev HealthDSA: Health Data Science and Analytics Community, Boston, Massachusetts, USA PubMed articles Google scholar articles
Yuan Lai Urban Science and Planning, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA PubMed articles Google scholar articles
Barbara D Lam Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA PubMed articles Google scholar articles
Megan Lipcsey Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA PubMed articles Google scholar articles
Alfonso Martinez Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA PubMed articles Google scholar articles
Oren J Mechanic Harvard Medical Faculty Physicians at Beth Israel Deaconess Medical Center Inc, Boston, Massachusetts, USA Emergency Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA PubMed articles Google scholar articles
Jack Mlabasati Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA PubMed articles Google scholar articles
Liam G McCoy Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada PubMed articles Google scholar articles
Freddy T Nguyen Massachusetts Institute of Technology, Boston, Massachusetts, USA PubMed articles Google scholar articles
Matthew Samuel Harvard University T H Chan School of Public Health, Boston, Massachusetts, USA PubMed articles Google scholar articles
Eric Yang Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA PubMed articles Google scholar articles
Leo Anthony Celi Harvard Medical Faculty Physicians at Beth Israel Deaconess Medical Center Inc, Boston, Massachusetts, USA Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA PubMed articles Google scholar articles

Correspondence to Dr Eva M Luo, OB/GYN, Harvard Medical Faculty Physicians at Beth Israel Deaconess Medical Center Inc, Boston, MA 02215, USA; eluo1{at}bidmc.harvard.edu

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Citation

Luo EM, Newman S, Amat M, et al

MIT COVID-19 Datathon: data without boundaries

BMJ Innovations 2021;7:231-234.

Publication history

Received June 30, 2020
Accepted August 14, 2020
First published August 31, 2020.

Online issue publication

January 19, 2021

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© Author(s) (or their employer(s)) 2021. No commercial re-use. See rights and permissions. Published by BMJ. This article is made freely available for use in accordance with BMJ’s website terms and conditions for the duration of the covid-19 pandemic or until otherwise determined by BMJ. You may use, download and print the article for any lawful, non-commercial purpose (including text and data mining) provided that all copyright notices and trade marks are retained.https://bmj.com/coronavirus/usage

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