AISC610 - Computationally-Enabled Medicine

Faculty: Paul Avillach and Isaac Kohane

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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.