University of Pittsburgh

Clinician-Focused Machine Learning

Associate Professor
Date: 
Friday, January 22, 2021 - 1:00pm - 1:30pm

Clinician-Focused Machine Learning 

 

Despite the huge interest in using machine learning techniques to improve health care, many models and systems succeed well in early stages, yet eventually fail when put into practice.  These unsuccessful efforts demonstrate the importance of centering the goals and workflow of the clinicians who must weigh computerized predictions and classifications alongside their own training and experience. Our efforts combine the exploration of novel problems in machine learning with qualitative inquiry into clinician information needs, preference, and workflow, to inform the design of novel tools and information presentation approaches aimed at successfully building machine learning into clinical practice.   Example projects discussing  predictions of patient outcomes, adaptive electronic medical records capable of highlighting high-value information, and identification of fine-grained disease subphenotyping will be used to illustrate our approach.  

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