Prediction of metabolic syndrome based on sleep and work-related risk factors using an artificial neural network

Prediction of metabolic syndrome based on sleep and work-related risk factors using an artificial neural network

Abstract Background Metabolic syndrome (MetS) is a major public health concern due to its high prevalence and association with heart disease and diabetes. Artificial neural networks (ANN) are emerging as a reliable means of modelling relationships towards understanding complex illness situations suc...

Full description

Bibliographic Details
Main Authors: Meysam Eyvazlou, Mahdi Hosseinpouri, Hamidreza Mokarami, Vahid Gharibi, Mehdi Jahangiri, Rosanna Cousins, Hossein-Ali Nikbakht, Abdullah Barkhordari
Format: Article
Language:English
Published: BMC 2020-11-01
Series:BMC Endocrine Disorders
Subjects:
Metabolic syndrome
Work-related stressors
Obstructive sleep apnea
Workplace
Modelling
Online Access:http://link.springer.com/article/10.1186/s12902-020-00645-x

Internet

http://link.springer.com/article/10.1186/s12902-020-00645-x

Similar Items