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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.
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 discussion, Harnessing Natural Language for Prediction and Prevention.
Jeffrey Girard, PhD, is an interdisciplinary researcher working to advance the behavioral sciences. His research into emotion, personality, and psychopathology draws insights and tools from social science, computer science, and data science. He received his PhD in clinical psychology from the University of Pittsburgh and is currently a post-doctoral research associate at Carnegie Mellon University.
Please visit mclean.org/itp to learn more about the McLean Institute for Technology in Psychiatry.
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