Computing with words and machine learning in medical diagnostics
The paper deals with the mathematical simulation of empirical learning in medical diagnostics. Such a simulation essentially amounts to solving both the problem of how to acquire, represent, and objectify the smallest typical units of diagnostic knowledge and the problem of how to identify the subje...
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| Published in | Information sciences Vol. 134; no. 1; pp. 53 - 69 |
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| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Inc
01.05.2001
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| Online Access | Get full text |
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| Summary: | The paper deals with the mathematical simulation of empirical learning in medical diagnostics. Such a simulation essentially amounts to solving both the problem of how to acquire, represent, and objectify the smallest typical units of diagnostic knowledge and the problem of how to identify the subject-specific situations in which diagnostic learning may take place at all. A solution to the first question will be provided by using so called fuzzy probabilities as a model. The second problem is solved by adequately formalizing that kind of knowledge as it is found in standard sources like textbooks for instance. |
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| Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 |
| ISSN: | 0020-0255 1872-6291 |
| DOI: | 10.1016/S0020-0255(01)00092-5 |