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Optimizing clinical practice with case‐based reasoning approach
Author(s) -
Dussart Claude,
Pommier Pascal,
Siranyan Valérie,
Grelaud Gilles,
Dussart Sophie
Publication year - 2008
Publication title -
journal of evaluation in clinical practice
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.737
H-Index - 73
eISSN - 1365-2753
pISSN - 1356-1294
DOI - 10.1111/j.1365-2753.2008.01071.x
Subject(s) - case based reasoning , model based reasoning , recall , computer science , artificial intelligence , opportunistic reasoning , chaining , adaptive reasoning , management science , knowledge representation and reasoning , psychology , cognitive psychology , psychotherapist , economics
Summary Rationale and aims Learning through experience is an important approach that humans employ to comprehend new problems. The knowledge of physicians does not only consist of rules, but of a mixture of textbook knowledge and experience. Medical treatment is facing a challenge of knowledge discovery from the growing volume of information. Method Case‐based reasoning (CBR) matches the natural reasoning model of human. This approach is similar to that used by physicians when they are thinking: ‘I have seen a patient like this’, and provides instant recollection of past cases that may be relevant to the present case. In fact, CBR is an approach for solving problems based on solutions of similar past cases. Unlike other forms of reasoning such as rule‐based reasoning, CBR does not draw conclusions by chaining together generalized rules. Conclusion The application of CBR to medical databases can be powerful techniques to aid physicians in making decisions about the management of their patients, in various types of medical units. CBR is an effective reasoning strategy for optimizing clinical practice.