Timely Detection of Diabetes with Support Vector Machines, Neural Networks and Deep Neural Networks
Author:
Valchev Rumen1, Nikolov Miroslav1, Nakov Ognyan2, Lazarova Milena2, Mladenov Valeri1
Affiliation:
1. Department Fundamentals of Electrical Engineering, Technical University of Sofia, Sofia, 8 St. Kliment Ohridski Blvd., BULGARIA 2. Faculty Computer Systems and Technologies, Technical University of Sofia, Sofia, 8 St. Kliment Ohridski Blvd., BULGARIA
Abstract
In this paper, we describe an expert system with three tools - Support Vector Machine (SVM), Deep Neural Network (DNN), and feed-forward neural network (NN) in MATLAB and Python to identify potential candidates with diabetes at the initial stages of the disease. To achieve this goal, the importance of the main factors associated with previous health problems and the onset of diabetes in individuals with a medical history is analyzed. By recognizing the common early indications of diabetes, the system can aid in the selection of patients and potentially benefit them by detecting the disease at an early stage and applying appropriate and timely healing.
Publisher
World Scientific and Engineering Academy and Society (WSEAS)
Subject
General Engineering,General Computer Science
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