Article 1419

Title of the article



Astaf'ev Andrey Nikolaevich, Assistant, sub-department of physics and biomedical technology, Lipetsk State Technical University (30 Moskovskaya street, Lipetsk, Russia), E-mail:
Gerashchenko Sergey Ivanovich, Doctor of engineering sciences, professor, head of sub-department of medical cybernetics and informatics, Penza State University (40 Krasnaya street, Penza, Russia), E-mail:
Yurkov Nikolay Kondrat'evich, Doctor of engineering sciences, professor, head of sub-department of radio equipment design and production, Penza State University (40 Krasnaya street, Penza, Russia), E-mail: 

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Background. The object of the study is a method of diagnosis of nosological forms of hepatitis using neural networks. The method of diagnosis is offered through the use of a decision support system. The decision support system allows you to solve complex decision-making tasks that require specialists’ experience, analyzing the accurate assessment of various alternative diagnoses, allowing you to analyze the predictive functionality.
Materials and methods. The authors applied a cascade correlation neural network with insisted topology for decision support system where the input data were serological markers and the output data were nosological forms of hepatitis.
Results. The researchers have developed the decision support system capable of diagnosing nosological forms of hepatitis based on the values of serological markers.
Conclusions. Decision support systems are an appropriate method for clinical decision-making, as they involve the processing of partial evidence and uncertainty about the effects of predicted interventions. 

Key words

decision support system, hepatitis nosology, serological markers, cascade correlation neural network 

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Дата создания: 12.03.2020 09:49
Дата обновления: 12.03.2020 10:14