MIT Department of Electrical Engineering & Computer Science

EECS Spring 1999 Catalogue Supplement

6.891 Medical Decision Support (H)

TR 11-12:30, 36-839
Prof. Peter Szolovits, NE43-416, x3476, Isaac Kohane, NE43-414, x3510, Lucila Ohno-Machado, E25-510, x9635
Prerequisite: 6.034 or HST 947; programming skills
3-0-9

This class presents the main concepts of decision analysis, artificial intelligence and predictive model construction and evaluation in the specific context of medical applications. It emphasizes the advantages and disadvantages of using these methods in real-world systems and provides hands-on experience. The technical focus is on decision analysis, knowledge-based systems (qualitative and quantitative), learning systems (including logistic regression, identification, neural networks), and techniques to evaluate the performance of such systems. Review of computer-based diagnosis, planning and monitoring of therapeutic interventions. Discussion of implemented medical applications and the software tools used in their construction. Students produce a final project using the methods learned in the class, based on actual clinical data.