Computationally-Enabled Medicine

Computational approaches to analyzing large data sets and applying the insights derived to clinical decision making are central to the present and future of biomedicine. This course will enable students to acquire a computational framework and toolkit for addressing this growing analytic challenge. Selected examples from genomics clinical decision making and from epidemiology informed by “big data” obtained from electronic healthcare data, claims data and even the social web will serve as the basis for exploration of the computational framework. Mentored experiences at medical data science companies and state-of-the-art clinical diagnostics enterprises will enable students to experience the application of and elaborate questions that can be addressed by computational biomedicine.

This course is only available for MD students at Harvard Medical School

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Associate Professor of Biomedical Informatics, Harvard Medical School
Assistant Professor of Pediatrics, Boston Children's Hospital
Assistant Professor in the Department of Epidemiology, Harvard T.H. Chan School of Public Health
Chair of the Department of Biomedical Informatics, Harvard Medical School
Marion V. Nelson Professor of Biomedical Informatics, Harvard Medical School
Associate Professor of Medicine, Brigham and Women's Hospital