Applications of computer science techniques such as data mining, machine learning and artificial intelligence have the potential to convert big data into clinically actionable knowledge. Successful biomedical informatics research projects require components of a data science pipeline that consists of data collection, storage, exploration, analysis, and visualization; however, many researchers enter the discipline with little to no computational expertise. While computer science courses may cover aspects of data science pipeline, they often have a theoretical focus or present the components in a disjoint manner. In this paper, we present our experience with designing and teaching a novel course focused on introducing trainees to the basic definitions, theories, and methods that serve as the foundations for biomedical computing.


Aditi Gupta (Presenter)
Washington University In St Louis

Tara Borlawsky-Payne (Presenter)
Washington University In St Louis

Sean Yu, Washington University In St Louis
Andrea Krussel, Washington University In St Louis
Philip Payne, Washington University In St Louis

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