Next: Introduction
Development of a Knowledge Base for Diagnostic Reasoning in
Cardiology
William J. Long,
MIT Laboratory for Computer Science, Cambridge, MA, USA
Shapur Naimi and M. G. Criscitiello
New England Medical Center Hospital, Boston, MA, USA
Reprinted from Computers
in Biomedical Research, 25: 292-311, 1992
Abstract:
This paper reports on a formative evaluation of the diagnostic
capabilities of the Heart Failure Program, which uses a probability
network and a heuristic hypothesis generator. Using 242 cardiac cases
collected from discharge summaries at a tertiary care hospital, we
compared the diagnoses of the program to diagnoses collected from
cardiologists using the same information as was available to the
program. With some adjustments to the knowledge base, the Heart Failure
Program produces appropriate diagnoses about 90%of the time on this
training set. The main reasons for the inappropriate diagnoses of the
remaining 10%include inadequate reasoning with temporal relations
between cause and effect, severity relations, and independence of acute
and chronic diseases.