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Biotechnical system based on fuzzy logic prediction for surgical risk classification using analysis of current-voltage characteristics of acupuncture points

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Journal of Integrative Medicine 2022年第3期20卷 252-264页

作者： Sergey Filist Riad Taha Al-Kasasbeh olga shatalova Nikolay Korenevskiy Ashraf Shaqadan Zeinab Protasova Maksim Ilyash Mikhail Lukashov Department of Biomedical Engineering Southwest State UniversityKursk 305040Russian Federation Electrical Energy Department Balqa Applied UniversityAmman 11937Jordan Civil Engineering Department Zarqa UniversityZarqa Governorate 13222Jordan Saint-Petersburg National Research University of Information Technologies Mechanics and OpticsSaint-Petersburg 197101Russian Federation Pediatric Faculty Kursk State Medical UniversityKursk 305041Russian Federation

Objective:This study aimed to develop expert fuzzy logic model to assist physicians in the prediction of postoperative complications of prostatic hyperplasia before ***:A method for classification of surgical risks was *** effect of rotation of the current–voltage characteristics at biologically active points(acupuncture points)was used for the formation of classifier *** effect determined reversible and non-reversible changes in electrical resistance at acupuncture points with periodic exposure to a sawtooth probe ***,the developed method was tested on the prediction of the success of surgical treatment of benign prostatic ***:Input descriptors were obtained from collected data including current-voltage characteristics of 5 acupuncture points and composed of 27 arrays feeding in the *** maximum diagnostic sensitivity of the classifier for the success of a surgical operation in the control sample was 88%and for testing data set prediction accuracy was 97%.Conclusion:The use of tuples of current-voltage characteristic descriptors of acupuncture points in the classifiers could be used to predict the success of surgical treatment with satisfactory *** model can be a valuable tool to support physicians’diagnosis.

关键词： Biologically active point Acupuncture Current-voltage characteristic Descriptor Neural network

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