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Applying Bayes' theorem in medical expert systems

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5 Author(s)
Chenglin Peng ; Inf. Eng. Coll., Chongqing Univ., China ; Shouzhong Xiao ; Zhiwei Nie ; Zhisheng Wang
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The authors think that the main problem with the application of Bayes' theorem in medical expert systems is that the formula itself cannot resolve the contradiction between frequency of disease manifestation and its specificity, especially for those manifestations that have a very low frequency but a high specificity. The authors have found in practice that the weighted summation method in its various application forms can handle these situations well. The diagnostic weight value of any manifestation can be adjusted by clinical experts, based on its actual importance for the diagnosis, as judged by theory and practical experiences. This method will be discussed more in detail in the authors' other paper. When adopting Bayes' method as the algorithm of a medical expert system, one must ensure that the theorem's two assumptions are satisfied as best as possible. There should be a sufficient quantity of cases of the diseases in the database, and the actual information should be as accurate as possible. When a system based on Bayes' formula is used in epidemiologically different populations, the a priori probability of the corresponding disease should be corrected. Especially, those manifestations with high specificity should be chosen as diagnostic indicators. In summary, applying Bayes' method can provide quite satisfactory results in many applications

Published in:

Engineering in Medicine and Biology Magazine, IEEE  (Volume:15 ,  Issue: 3 )

Date of Publication:

May/Jun 1996

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