The raising of the efficiency of the computer's model diagnostics with the help of artificial neural network

Authors

  • Ольга Игоревна Соловьева Kozhedub Air Force university 77/79 Sumska str, Kharkiv, Ukraine, 61023, Ukraine

DOI:

https://doi.org/10.15587/2312-8372.2013.18399

Keywords:

mathematical model, artificial neural network, diabetes

Abstract

The method for automated objective early diagnostics of latent type 2 diabetes (D2) of an examined patient based on computeraided model processing of his/her oral glucose tolerance test (OGTT) results using artificial neural network (ANN) was suggested. It is known that D2, accompanied by deadly late vascular and neurological complications, is a widespread disease, especially in developed countries, and constitutes a serious medical and social problem. Nowadays, the most precise diagnostics of latent D2 is the expert diagnosis of experienced endocrinologist on glycaemic results of the OGTT. However, it has a subjective nature and cannot be used for conducting mass health examinations, the need for which has increased lately.

Thus, the problem of developing the method of automated objective early D2 diagnostics based on computeraided processing of the patient’s glycaemic results of the OGTT with differentiation of diagnosed conditions is urgent. Possible applications of both artificial neural networks and mathematical modeling were demonstrated in literature. Thus, it was found that each of the methods of computeraided diagnostic processing of OGTT results has significantly less sensibility in detecting latent diabetes, comparing to the doctor’s. The paper shows that the combined application of computer modeling and ANN in processing the patient’s glycaemic results allows approximating the sensibility of automated objective early D2 detection to the expert endocrinologist’s diagnosis.

Author Biography

Ольга Игоревна Соловьева, Kozhedub Air Force university 77/79 Sumska str, Kharkiv, Ukraine, 61023

Instructors  

Department of the Computer networks and systems

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Published

2013-10-30

How to Cite

Соловьева, О. И. (2013). The raising of the efficiency of the computer’s model diagnostics with the help of artificial neural network. Technology Audit and Production Reserves, 5(2(13), 36–39. https://doi.org/10.15587/2312-8372.2013.18399

Issue

Vol. 5 No. 2(13) (2013): Production reserves

Section

Production reserves

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Copyright (c) 2016 Ольга Игоревна Соловьева

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