"Natural Language Processing and Machine Learning Applications in Medicine"

A major component of natural language processing in medicine involves understanding the full meaning of textual data to provide useful information for providers and patients. Textual data is readily available in electronic health records, including radiology reports. In clinical medicine, information derived from these data sources informs providers when making clinical decisions as well as provides structured information for evaluating initiatives focused on patient safety and quality of care. This talk will describe developed and validated Natural Language Processing (NLP), information extraction and data analytic systems that employ machine learning and traditional statistical approaches. Feature selection and combination will be described, using unsupervised and supervised algorithms. Finally, evaluation frameworks will be presented to compare various models and approaches.

Ronilda Lacson, M.D., Ph.D.
Assistant Radiology Professor
Harvard Medical School
Brigham and Woman's Hopsital
Brookline, MA

Amy Kuceyeski, Ph.D.
Associate Radiology and Neuroscience Mathematics Professor, Weill Cornell Medicine
Adjunct Assistant Biological Statistics and Computational Biology Professor, Cornell University
amk2012@med.cornell.edu

Mert Rory Sabuncu, Ph.D.                           
Assistant Electrical and Computer Engineering Professor
Cornell University School of Biomedical Engineering
ms3375@cornell.edu​​​​​​​

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Meeting ID: 868 469 115
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