CLINICAL USE OF INFORMATION PROCESSING AND ANALYSIS SYSTEM BASED ON ARTIFICIAL NEURAL NETWORK OF “MULTILAYER PERCEPTRON” TYPE

S V Fedorov , M Sh Kashaev , T R Kashaev

Perm Medical Journal ›› 2013, Vol. 30 ›› Issue (4) : 97 -102.

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Perm Medical Journal ›› 2013, Vol. 30 ›› Issue (4) :97 -102. DOI: 10.17816/pmj30497-102
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CLINICAL USE OF INFORMATION PROCESSING AND ANALYSIS SYSTEM BASED ON ARTIFICIAL NEURAL NETWORK OF “MULTILAYER PERCEPTRON” TYPE

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Abstract

Aim. To improve the results of surgical treatment of patients with thyroid gland pathology by means of developing electronic computer (EC) program allowing to optimize diagnosis, observation and prognosis of the disease course. Materials and methods. Together with the Chair of Computer Engineering and Information Security of Ufa State Aviation and Technical University the program “Intellectual System for Diagnosis of Thyroid Pathology Based on Neuronet Technologies” was developed. Results. The authors worked out and registered EC program “Intellectual System for Diagnosis of Thyroid Pathology Based on Neuronet Technologies” permitting to collect, store and analyze information on patients. The program is also capable of presenting the supposed diagnosis and result of treatment on the basis of the introduced information. Analysis of 148 case histories and ambulatory records of patients with diffuse toxic goiter was carried out; accuracy of diagnosis was > 90%; accuracy of disease outcome prediction was >75%. Conclusion. The applied modern methods of diagnosis and processing of the obtained data by means of biomedical statistics as well as neuronet information processing and analysis system make it possible to optimize patients’ management, storage and processing of medical information and permits to conduct differential diagnosis of diseases.

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Thyroid gland / artificial neural network / diagnosis

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S V Fedorov, M Sh Kashaev, T R Kashaev. CLINICAL USE OF INFORMATION PROCESSING AND ANALYSIS SYSTEM BASED ON ARTIFICIAL NEURAL NETWORK OF “MULTILAYER PERCEPTRON” TYPE. Perm Medical Journal, 2013, 30(4): 97-102 DOI:10.17816/pmj30497-102

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Fedorov S.V., Kashaev M.S., Kashaev T.R.

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