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- W2110233735 abstract "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." @default.
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- W2110233735 date "2000-01-01" @default.
- W2110233735 modified "2023-09-28" @default.
- W2110233735 title "A Neuro-Fuzzy Approach as Medical Diagnostic Interface" @default.
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