UDK: 616-33-002.44+616.366-002+616.37-002:616-084]004.032.26

APPLICATION OF ARTIFICIAL NEURAL NETWORKS FOR DIFFERENTIAL DIAGNOSIS AND PROPHYLAXIS OF THE DISEASES OF HEPATOPANCREATODUODENAL ZONE

V.A. Lazarenko1, T.V. Zarubina2, A.E. Antonov1, D.A. Cervantes Barragan3

1ФГБОУ ВО «Курский государственный медицинский университет» Министерства здравоохранения Российской Федерации, кафедра хирургических болезней ФПО; 2ФГБОУ ВО «Российский национальный исследовательский медицинский университет имени Н.И. Пирогова» Министерст

Abstract

The purpose of the study was to evaluate the possibilities of neuronet differential diagnosis of hepatopancreatoduodenal zone diseases and their potential for the formation of an individualized preventive strategy. The work was performed on the basis of materials of 488 patients with the pathology of the hepatopancreatoduodenal zone. Neural network analysis of information on risk factors (sex, age, eating habits, stress, family status, bad habits) was used. Results. The sensitivity of the differential diagnostic model reaches Se = 84,7, m = 1,66 for peptic ulcer, Se = 81,4, m = 1,8 for pancreatitis and Se = 92,1, m = 1,24 for cholecystitis. Specificity levels equaled respectively to Sp = 91,5, m = 1,29, Sp = 90,1, m = 1,38 and Sp = 82,7, m = 1,75. The article also presents a method of developing an individualized diagnostic strategy using the artificial neural network.

Keywords

risk factors, hepatopancreatoduodenal zone, diagnosis, prophylaxis, software.

Contacts

Лазаренко Виктор Анатольевич – д. м. н., профессор, ректор, заведующий кафедрой хирургических болезней ФПО, Курский государственный медицинский университет, e-mail: lazarenkomed@mail.ru