6.872 Biomedical Computing
Analyzes computational needs of clinical medicine, reviews systems and approaches that have been used to support those needs, and the relationship between clinical data and gene and protein measurements to support precision medicine. Topics include the nature of clinical data, architecture and design of healthcare information systems, privacy and security issues, medical expert systems, predictive models and machine learning from big data in healthcare, and an introduction to bioinformatics. Case studies and guest lectures describe contemporary institutions, systems, and research projects. Term project using large clinical and genomic data sets integrates classroom topics.
Lecture occurs 9:30 AM to 11:00 AM on Mondays and Wednesdays in 36-155.
This class counts for a total of 12 credits.
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