Intelligent Classification and Diagnosis of Diabetes and Impaired Glucose Tolerance Using Deep Neural Networks

Author:

Alanis Alma Y.1ORCID,Sanchez Oscar D.1,Vaca-González Alonso2,Rangel-Heras Eduardo1

Affiliation:

1. University Center of Exact Sciences and Engineering, University of Guadalajara, Guadalajara 44430, Mexico

2. Institutional Safety, Health and Environment System (SISSMA), University of Guadalajara, Guadalajara 44430, Mexico

Abstract

Time series classification is a challenging and exciting problem in data mining. Some diseases are classified and diagnosed based on time series. Such is the case for diabetes mellitus, which can be analyzed based on data from the oral glucose tolerance test (OGTT). Prompt diagnosis of diabetes mellitus is essential for disease management. Diabetes mellitus does not appear suddenly; instead, the patient presents symptoms of impaired glucose tolerance that can also be diagnosed via glucose tolerance testing. This work presents a classification and diagnosis scheme for diseases, specifically diabetes mellitus and poor glucose tolerance, using deep neural networks based on time series data. In addition, data from virtual patients were obtained through the Dalla Man and UVA/Padova models; the validation was carried out with data from actual patients. The results show that deep neural networks have an accuracy of 96%. This indicates that DNNs is a helpful tool that can improve the diagnosis and classification of diseases in early detection.

Publisher

MDPI AG

Subject

General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. AIoT-Powered Intelligent Remote Patient Activity Tracking and Comprehensive Vital Sign Analysis System for Enhanced Healthcare;Advances in Medical Technologies and Clinical Practice;2024-06-21

2. Optimization Methods for Random Forest Models in Early Diabetes Prediction;2023 4th International Conference on Computer, Big Data and Artificial Intelligence (ICCBD+AI);2023-12-15

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