Data Science I
Data Science for Medical Decision Making
There is a need to prepare translational informatics researchers to repurpose large and observational biomedical population-based datasets for data-driven discovery. These datasets may include, but are not limited to observational epidemiological cohorts, medical health claims, and electronic medical records, for biomedical discovery. This course will survey the current data and methodological approaches to conduct integrative high-throughput investigation merging genomic, exposomic, and phenomic modalities to find new associations in disease and prevention.
Students will be encouraged to find publicly available population data, such as those available from the Databases of Genotypes and Phenotypes, US Centers for Disease Control and Prevention, and USAID. Students may be given sample de-identified extracts from medical claims or electronic health record datasets. Students will also be encouraged to formulate a research paper for submission to a journal or as a proceedings article.
Open to all Harvard and MIT students. To enroll, email CV and brief statement of interest to Rebecca Fitzhugh.