Title :
Combination of a neural network model and a rule-based expert system to determine efficacy of medical testing procedures
Author :
Cohen, M.E. ; Hudson, D.L. ; Anderson, M.F.
Author_Institution :
California State Univ., Fresno, CA, USA
Abstract :
A medical decision-support system that combines a neural network model with expert-derived rules in an attempt to bring all relevant factors to bear in designing testing strategies is discussed. The system is illustrated with data from a study on testing modalities in the diagnosis, treatment, and staging of carcinoma of the lung. The results are illustrated using the decision of whether or not to perform thoracotomy. A sample neural network is shown for the surgery/no-surgery decision
Keywords :
decision support systems; expert systems; lung; medical diagnostic computing; neural nets; physiological models; surgery; carcinoma; diagnosis; efficacy; expert-derived rules; lung; medical decision-support system; medical testing procedures; modalities; neural network model; rule-based expert system; staging; surgery decision; thoracotomy; treatment; Artificial neural networks; Data mining; Decision making; Lungs; Medical diagnostic imaging; Medical expert systems; Medical tests; Neural networks; Supervised learning; System testing;
Conference_Titel :
Engineering in Medicine and Biology Society, 1989. Images of the Twenty-First Century., Proceedings of the Annual International Conference of the IEEE Engineering in
Conference_Location :
Seattle, WA
DOI :
10.1109/IEMBS.1989.96560
