METHOD OF DIFFERENTIAL DIAGNOSTICS OF THE NOSOLOGICAL FORM OF VIRAL HEPATITIS WITH THE APPLICATION OF NEURAL NETWORK OF CASCADE CORRELATION

UDC 004.891.3
DOI:10.26102/2310-6018/2019.26.3.028

A.N. Astafev


An important aspect of determining the nosological form of hepatitis is the combination of input data at the beginning of the study. The use of neural networks in medicine, which have the ability to search for hidden dependencies by learning from the experience of doctors, makes it easier to work in the role of advisor. However, the question of selecting the most effective topology for a specific task remains open. This paper substantiates the need to use neural network algorithms to solve the problem of determining the nosological form of hepatitis. The analysis and selection of input factors characterizing the clinical condition of the patient, and output factors characterizing the specific nosological form of hepatitis, neural network. The algorithm, its use is described, and a cascade neural network is compared with others in the context of the problem under consideration. At the end, a description is made of the established system for determining the nosological form of hepatitis using a cascade correlation neural network, and also describes the clinical efficacy.

Keywords: neural network, viral hepatitis, nosological form of hepatitis, neural network of cascade correlation, classification.

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