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Application of fuzzy neural network model and current-voltage analysis of biologically active points for prediction post-surgery risks

Author

Listed:
  • Olga Shatalova
  • Sergey Filist
  • Nikolay Korenevskiy
  • Riad Taha Al-kasasbeh
  • Ashraf Shaqadan
  • Zeinab Protasova
  • Maksim Ilyash
  • Anatoly Rybochkin

Abstract

The work investigates neural network model for prediction of post-surgical treatment risks. The descriptors of the risk classifiers are formed on the basis of the analysis of the current-voltage characteristics of one, two and three biologically active points. The training and verification samples were formed by examining 120 patients with a diagnosis of benign prostatic hyperplasia. Of these, 62 patients were successfully operated on (class C1), 30 had various complications after surgery (class C2), 28 patients required additional treatment (class C3). The constructed classifiers showed a high quality of predicting critical conditions during surgical treatment.

Suggested Citation

  • Olga Shatalova & Sergey Filist & Nikolay Korenevskiy & Riad Taha Al-kasasbeh & Ashraf Shaqadan & Zeinab Protasova & Maksim Ilyash & Anatoly Rybochkin, 2021. "Application of fuzzy neural network model and current-voltage analysis of biologically active points for prediction post-surgery risks," Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis Journals, vol. 24(13), pages 1504-1516, October.
    • Handle: RePEc:taf:gcmbxx:v:24:y:2021:i:13:p:1504-1516
    DOI: 10.1080/10255842.2021.1895128
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