June 20, 2018 | 3:30pm - 5pm
Reception to follow
Light refreshments provided
NCRC Research Auditorium
2800 Plymouth Road
Ann Arbor, 48109
The Challenge of Medical Artifical Intelligence
Medicine presents a particular problem for creating artificial intelligence (AI), because the issues and tasks involved are surprisingly subjective. Valid and useful AI requires not only reliable, unbiased, and extensive data, but also objective definitions and intentions. Assistance is most needed in day-to-day complex decision-making that requires data synthesis and integration, tasks we now approach with clinical intuition. This process is generally accepted as representing the ‘art’ of medicine despite being riddled with cognitive biases and often based on large information gaps. Resolving the subjectivity of medicine with the objectivity required for digitization—and the secondary creation of AI—first involves resolution of a number of questions: What do we want to do? What do we need to do? What can we do?
About Leo Celi:
Leo Anthony Celi has practiced medicine in three continents, giving him broad perspectives in healthcare delivery. As clinical research director and principal research scientist at the MIT Laboratory for Computational Physiology (LCP), and as an attending physician at the Beth Israel Deaconess Medical Center (BIDMC), he brings together clinicians and data scientists to support research using data routinely collected in the process of care. His group built and maintains the public-access Medical Information Mart for Intensive Care (MIMIC) database, which holds clinical data from over 60,000 stays in BIDMC intensive care units (ICU). It is an unparalleled research resource; over 5000 investigators from more than 70 countries have free access to the clinical data under a data use agreement. In 2016, LCP partnered with Philips eICU Research Institute to host the eICU database with more than 2 million ICU patients admitted across the United States.
Leo also founded and co-directs Sana, a cross-disciplinary organization based at the Institute for Medical Engineering and Science at MIT, whose objective is to leverage information technology to improve health outcomes in low- and middle-income countries. He 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. The textbook “Secondary Analysis of Electronic Health Records” came out in October 2016 and was downloaded more the 100,000 times in the first year of publication. The massive open online course HST.936x “Global Health Informatics to Improve Quality of Care” was launched under edX in February 2017. Finally, Leo has spoken in 25 countries about the value of data in improving health outcomes.