The Utility of Artificial Neural Networks for the Non-Invasive Prediction of Metabolic Syndrome Based on Personal Characteristics

The Utility of Artificial Neural Networks for the Non-Invasive Prediction of Metabolic Syndrome Based on Personal Characteristics

This study investigated the diagnostic accuracy of using an artificial neural network (ANN) for the prediction of metabolic syndrome (MetS) based on socioeconomic status and lifestyle factors. The data of 27,415 subjects who went through examinations and answered questionnaires during three stages f...

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Bibliographic Details
Main Authors: Feng-Hsu Wang, Chih-Ming Lin
Format: Article
Language:English
Published: MDPI AG 2020-12-01
Series:International Journal of Environmental Research and Public Health
Subjects:
metabolic syndrome
artificial neural network
lifestyle factors
socioeconomic status
Online Access:https://www.mdpi.com/1660-4601/17/24/9288

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