TY  - JOUR
A1  - Brause, Rüdiger W.
A1  - Friedrich, F.
T1  - A neuro-fuzzy approach as medical diagnostic interface
N2  - In contrast to the symbolic approach, neural networks seldom are designed to explain what they have learned. This is a major obstacle for its use in everyday life. With the appearance of neuro-fuzzy systems which use vague, human-like categories the situation has changed. Based on the well-known mechanisms of learning for RBF networks, a special neuro-fuzzy interface is proposed in this paper. It is especially useful in medical applications, using the notation and habits of physicians and other medically trained people. As an example, a liver disease diagnosis system is presented.
Y1  - 2010
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/7965
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30-79176
N1  - Postprint, zuerst in: European Symposium on Artificial Neural Networks, ESANN 2000, D-Facto, Brussels, 2000, S. 201-206
ER  -