Artificial Intelligence in Medicine and Biology

ICS 691 Sec 2 - Fall 2013 - Topics in Software - Homepage

Quick Links: Messages , Schedule, Course Description (pdf), Projects , Presentation Evaluation Form,
Instructor: Prof. Nancy Reed, 314E POST,, (808) 956-8498.
Office hours Mon & Wed 11:45-12:30 or by appointment.
Lectures: Mon and Wed 10:30-11:45 am, POST 318B.


This course gives students an overview of Artificial Intelligence (AI) techniques used in medicine and biology. Practical applications of AI range from decision support systems for diagnosis to modeling physiologic processes, to analyzing human and animal DNA. Students in the course gain an in-depth practical experience by completing a course project on a topic of their choice.


Texts: Optional texts: Artificial Intelligence, A Modern Approach, 3rd Edition, by Stuart Russell & Peter Norvig, Prentice Hall, 2009.
Paradigms of Artificial Intelligence Programming: Case Studies in Common Lisp, by Peter Norvig, Morgan Kaufmann, 1st edition, 1991.
Readings in Medical Artificial Intelligence: The First Decade Edited by William J. Clancey and Edward H. Shortliffe, Addison Wesley, Reading, MA, 1984, Out of print. All chapters are freely available at
Biomedical Informatics: Computer Applications in Health Care and Biomedicine, Edward H. Shortliffe and James J. Cimino (Editors) 3rd Edition, Springer, 2006, ISBN-10: 0387289860, ISBN-13: 978-0387289861. Note: 4th edition expected this Fall.
Rule-Based Expert Systems: The MYCIN Experiments of the Stanford Heuristic Programming Project Edited by Bruce G. Buchanan and Edward H. Shortliffe, Addison Wesley, Reading, MA, 1984. Out of print. All chapters are freely available at:

Other material:Selected papers from books, journals and conferences including the Artificial Intelligence in Medicine journal, Journal of the American Medical Informatics Association (AMIA),and AAAI/ACM/IEEE journals and conferences. Papers will typically be available online through the library or will be provided as handouts.

Course Requirements

Grades are based on participation in class discussions and the presentation of technical papers (25%) and a term project including proposal, progress report, a final presentation and a final report (75%).

Back to the Top of this page

(c) N. E. Reed, 2005-2013