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Cheryl Corcoran, MD, is a graduate of Harvard College and Harvard Medical School. She is an associate professor of Psychiatry and program leader in Psychosis Risk at the Icahn School of Medicine at Mount Sinai. Together with Dr. Guillermo Cecchi of IBM, Dr. Corcoran has identified linguistic predictors of later psychosis onset in youths at clinical risk for psychosis using natural language processing algorithms and machine learning. She now has NIMH funding to study the underlying neural mechanisms of language disturbance across the psychosis spectrum, and to characterize demographic and cognitive correlates of language.
These remarks were part of the 2018 Technology in Psychiatry Summit, an event sponsored by the McLean Institute for Technology in Psychiatry, which occurred November 1-2, 2018 at Harvard Medical School, Boston, Massachusetts. Part of panel on Harnessing Natural Language for Prediction and Prevention.
Themes/keywords: prediction and prevention using technology; natural language processing; linguistic predictors of mental health; mining electronic health records; translation of tools or methodologies between languages or cultural contexts.
Human communication is at the core of all clinical interactions, especially in psychiatry and psychology, since changes in social function and use of language are often among the first noticeable clues of an emerging psychiatric illness or impending episode. Systems that capture and analyze naturally occurring speech or written language could therefore have transformative potential to aid in low-burden mental health surveillance strategies to support individuals most at risk with both prediction and optimal prevention strategies. This session brings together experts in both computational aspects of natural language processing (NLP), and their deployment in a range of psychiatric illnesses and treatment contexts, including mining electronic medical records for risk stratification, analyzing text-based encounters with a crisis coach to optimize online therapeutic encounters, and predicting individual-level prognosis from open and directed samples of speech and writing.
Please visit mclean.org/itp to learn more about the McLean Institute for Technology in Psychiatry.
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