Medical Decision Support
MIT OpenCourseWare offers this graduate course on decision analysis, artificial intelligence, and predictive modeling for clinical applications. Lectures from Stephan Dreiseitl, Ju Jan Kim, Bill Long, Marco Ramoni, Fred Resnic, and David Wypij cover knowledge-based systems, logistic regression, classification trees, neural networks, and rough sets, along with methods to evaluate how well these systems perform. The course reviews computer-based diagnosis, treatment planning, and patient monitoring, and looks at software tools used in real deployed medical systems. Students work with actual clinical data to build a final project applying the machine learning techniques covered in class. Materials include lecture notes and assignments through MIT's OpenCourseWare site, free to access with no certificate offered. It suits students with some background in statistics or computing who want to see how algorithmic decision-making gets applied to real patient care problems.