Artifcial intelligence capabilities in evaluating effectiveness of non-medicinal treatment of obesity in children
https://doi.org/10.33667/2078-5631-2022-18-20-24
Abstract
Introduction. Non-drug therapy for obesity cannot always guarantee a positive result, which forces doctors and scientists from all over the world to look for new methods for analyzing the effectiveness of treatment, including using artifcial intelligence. Its active implementation can significantly improve the quality of diagnosis and prognosis of the disease. Purpose of the study. To evaluate the possibilities of using the artifcial intelligence system in predicting the effectiveness of non-drug therapy for obesity in children.
Materials and methods. An artifcial neural network was built using the Statistica Neural Networks software package based on data from patients who were hospitalized at the Voronezh Children's Clinical Hospital of the VSMU n.a. N.N. Burdenko.
Results. The study group included 60 children (30 boys and 30 girls), aged 8 to 16 years. We selected the parameters that, in our opinion, have the most signifcant impact on the effect of non-drug treatment of obesity: the presence and frequency of inpatient treatment; obesity complications; compliance with the regime of physical activity and dietary recommendations; dynamics of body weight during non-drug treatment. After training, the neural network MLP 5-5-1 was selected with determination coeffcients of 0.925231; 0.981940; 0.936712 for training, test and control samples. The learning error is 0.105782, the learning algorithm is BFGS. The activation function of hidden neurons is hyperbolic, and the output function is identical.
Conclusion. The results of the study show that an artifcial neural network can be used to evaluate the effectiveness of non-drug treatment with a minimum error.
About the Authors
T. V. Chubarov
Voronezh State Medical University n.a. N.N. Burdenko
Russian Federation
Russian Federation
Chubarov Timofei V., PhD Med, chief physician of Voronezh Children's Clinical Hospital, director of Endocrinological Centre
Voronezh
O. A. Zhdanova
Voronezh State Medical University n.a. N.N. Burdenko
Russian Federation
Russian Federation
Zhdanova Olga A., DM Sciences (habil.), associate professor at Dept of Clinical Pharmacology
Voronezh
O. G. Sharshova
Voronezh State Medical University n.a. N.N. Burdenko
Russian Federation
Russian Federation
Sharshova Olga G., head of Dept of Endocrinology of Voronezh Children's Clinical Hospital
Voronezh
O. G. Galda
Voronezh State Medical University n.a. N.N. Burdenko
Russian Federation
Russian Federation
Galda Olga G., 6th year student
Voronezh
M. V. Patritskaya
Voronezh State Medical University n.a. N.N. Burdenko
Russian Federation
Russian Federation
Patritskaya Maria V., doctor of ultrasound diagnostics of Voronezh Children's Clinical Hospital
Voronezh
K. S. Niftaliev
Voronezh State Medical University n.a. N.N. Burdenko
Russian Federation
Russian Federation
Niftaliev Kenan S., 5th year student
Voronezh
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Review
For citations:
Chubarov T.V., Zhdanova O.A., Sharshova O.G., Galda O.G., Patritskaya M.V., Niftaliev K.S. Artifcial intelligence capabilities in evaluating effectiveness of non-medicinal treatment of obesity in children. Medical alphabet. 2022;1(18):20-24. (In Russ.) https://doi.org/10.33667/2078-5631-2022-18-20-24
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