Capabilities of neural network technologies for extracting new medical knowledge and enhancing precise decision making for patients

Abstract

ABSTRACT Objectives Currently, there is an active use of neural networks in various areas of human activity. Problems of recognition, diagnostics, optimization, forecasting, control, as well as obtaining new scientific knowledge are successfully solved. However, in medicine, due to the particular complexity of the human body, neural networks are mainly used only for solving the simplest problems of classification and diagnostics. The purpose of this article is to show that the possibilities of neural network modeling in medicine are much wider. Methods This goal is achieved by using special mathematical techniques developed by the authors that allow us to overcome these difficulties. Results The intellectual system created in this way made it possible to reveal a number of interesting scientific knowledge, which sometimes does not coincide with the generally accepted ideas of doctors. Virtual experiments conducted on computer models of patients using our intelligent system clearly demonstrate which lifestyle and medication variations can benefit a particular patient in the long term, and which can cause harm. Conclusion Our intellectual system allows us to identify new scientific knowledge, to carry out long-term forecasting of the development of the disease, to select the optimal courses of treatment and prevention of diseases.