2020台灣生技月 Bio Taiwan 生物科技大展

2020 台灣生技月 南港展覽館

講師

Leo Anthony Celi

Session 14 – AI and Smart Healthcare
Date: 24 July (Friday) 15:40 – 17:10 (GMT+8)
Venue: 701EF, 7F, TaiNEX2 / Online event platform


Leo Anthony Celi

Principal Research Scientist
Massachusetts Institute of Technology


As clinical research director at the MIT Laboratory for Computational Physiology, and as a practicing intensive care unit physician at the Beth Israel Deaconess Medical Center, Leo brings together clinicians and data scientists to support research using data routinely collected in the process of care. His group built and maintains the publicly-available Medical Information Mart for Intensive Care (MIMIC) database and the Philips-MIT eICU Collaborative Research Database, with more than 12,000 users from around the world. MIMIC-III has been cited more than 1500 times since 2016. In addition, Leo is one of the course directors for HST.936 – global health informatics to improve quality of care, and HST.953 – collaborative data science in medicine, both at MIT. He is an editor of the textbook for each course, both released under an open access license. "Secondary Analysis of Electronic Health Records" has been downloaded more than 500,000 times, and has been translated to Mandarin, Spanish and Korean. Finally, Leo has spoken in more than 35 countries across 6 continents about the value of data and learning in health systems.


Speech title & Synopsis

Battling the Pandemic with Open Science and Cross-Disciplinary Collaboration

COVID-19 is a formidable global threat, impacting all aspects of society and exacerbating the existing inequities of our current social systems. As we battle the virus across multiple fronts, data are critical for understanding this disease and for coordinating an effective global response. Given the current digitization of so many aspects of life, we are amassing data that can be extrapolated and analyzed for the effective forecasting, prevention, and treatment of COVID-19. Learning from the data, responsibly and across disciplines, in combination with communication, education, treatment, and policy decisions, are our best ways forward to defeat this virus while laying the groundwork for collaborative data science in the face of future calamity.