Connectionist expert systems as medical decision aid

摘要

In this paper neural networks are used as associative memories to build an expert system for aiding medical diagnosis. As in expert systems using symbolic manipulation, the knowledge is introduced by a knowledge engineer using a collection of known cases. The system has an object-oriented approach to knowledge organization and the resulting network topology. Fuzzy sets are used to interpret connection values and/or excitation state of the units. The main result is that the proposed neural network allows not only finding a solution in some cases, but also suggests obtaining more clinical data if the data available is insufficient to reach a conclusion. This approach is illustrated by examples.