A model-based system to determine the relative value of different variables in a diagnostic system using Bayes theorem |
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| Institution: | 1. Department of General Surgery, The Second Affiliated Hospital of Shanghai University (Wenzhou Central Hospital), Wenzhou, Zhejiang, 325000, China;2. Department of Hepatobiliary, Pancreatic and Minimally Invasive Surgery, Zhejiang Provincial People''s Hospital, Hangzhou, 310014, China;3. Department of Information Technology, Wenzhou Polytechnic, Wenzhou, 325035, China;4. Department of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou, 325035, China;5. Department of Information Technology, College of Computers and Information Technology, Taif University, P.O. Box 11099, Taif, 21944, Taif, Saudi Arabia;6. Department of Computer Science, Birzeit University, Birzeit, 72439, Palestine;7. The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, PR China;1. Clinical Trial Center, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China;2. National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin, China;3. Graduate School, Tianjin University of Traditional Chinese Medicine, Tianjin, China;4. Graduate School, Henan University of Chinese Medicine, Zhengzhou, Henan, China |
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| Abstract: | A model system is described which simulates the presenting features of cases of vaginal discharge. This system was used to examine the effects of removing individual clinical features on the overall efficiency of diagnosis by Bayes theorem. The diagnostic efficiency was significantly reduced by elimination of inflammation, of a frothy discharge, or of a curdy discharge. Elimination of more than one significant factor further reduced the number of correct diagnoses, but elimination of more than one non-significant factor made no obvious difference. The most significant clinical feature was presence of inflammation; elimination of this feature had a substantial effect on the diagnosis of gardnerella, viral, gonorrhoea and foreign body. Elimination of two of the variables (bloodstaining and odour) which did not influence overall diagnostic efficiency nevertheless had a substantial effect on the diagnosis of neoplasms and foreign bodies. It is proposed that a simulation of this type is of potential practical value in determining a minimum subset of clinical features for diagnostic systems involving Bayes theorem. |
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