Progressive artificial neural network for medical applications

Authors

  • Boris Farber Farber’s Center for Academic Success, Inc, New York, NY, USA, United States
  • Vladimir Proseanic Progress, INC. West Bloomfield MI, USA: Omega Server Inc., West Bloomfield MI, USA, United States
  • Boris Zlotin Progress, INC. West Bloomfield MI, USA: Omega Server Inc., West Bloomfield MI, USA, United States
  • Artur Martynov Mechnikov Institute of microbiology and immunology, Ukraine

Abstract

This article is presented by professionals, working in diverse fields and combining their knowledge in artificial neural networks with decades of experience in application of TRIZ, the Theory of Inventive Problem Solving. The article describes problems associated with the impossibility of effectively using existing neural networks for the analysis of medical information. Their solution proposes utilization of the recently invented, fundamentally new system - Progressive Artificial Neural Network (PANN). A description of PANN and its advantages is presented. The example of PANN implementation is shown with some possible applications of PANN, together with TRIZ, for conducting important research in the field of medicine, invention, and the development of new medical equipment and diagnostic and treatment methods. In particular, the authors propose:

  • Intelligent Database Management System in Medicine (IDBMSM),
  • System "Medical Advisor"
  • System "Personal Physician"
  • System "Physician Assistant - Researcher"
  • Medical Control System “Identify an error (mistake)”
  • System "Development of medical technology"
  • System of mass medical monitoring
  • Medical training system

The authors believe that the use of the PANN system will be a very important step in the development of both the theory and practical aspects of medicine.

DOI: 10.5281/zenodo.5767065

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Published

2021-12-09

How to Cite

Farber, B., Proseanic, V., Zlotin, B. ., & Martynov, A. . (2021). Progressive artificial neural network for medical applications. Annals of Mechnikov’s Institute, (4), 91–100. Retrieved from https://journals.uran.ua/ami/article/view/246527

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Section

Research Articles