Electrical Engineering and Computer Science

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Fall 2011: Computation for Predictive and Personalized Medicine

Course No.: EECS598
Credit Hours: 3
Instructor: Zeeshan Syed
Prerequisites: EECS281/STATS412 (or equivalent with permission of instructor)

Course Description:
This course provides a multi-disciplinary, hands-on introduction to designing computational systems to address the needs of modern medicine, through real-world projects and clinical/industrial partners. The goal of this course is to develop the knowledge and skills needed to create computational systems for predictive and personalized medicine that can have translational impact in different application domains (e.g., cardiology, psychiatry, critical care). The class consists of lectures and discussions, with students focusing on a semester long project to develop a solution to an important clinical challenge in close collaboration with local partners who are experts in relevant fields. Topics include the main concepts of decision analysis, predictive modeling, data management, biostatistics, and disease pathophysiology. Emphasis will be placed on the advantages and disadvantages of using these methods in real-world systems.