Use of the Method of Configuring the Interval Target in the Problem of Synthesis of the Neural Network Classifier for Diagnosing Cardiovascular Diseases

Abstract

A new approach of using the paradigm of “interval teacher” in the classical scheme of training neural networks with a teacher is used to solve the problem of medical diagnosis of the disease coronary heart disease. An NN architecture has been created that implements a mechanism for selecting a specific “teacher” from a deterministic interval set. A comparative analysis of the proposed and classical training schemes of the neural network is shown, confirming the effectiveness of the proposed training concept. The created medical classifier based on a neural network with an interval teacher provides high classification accuracy.