Prediction Effects of Personal, Psychosocial, and Occupational Risk Factors on Low Back Pain Severity Using Artificial Neural Networks Approach in Industrial Workers.

Journal: Journal of manipulative and physiological therapeutics

Published Date: Sep 1, 2017

Abstract

OBJECTIVES: This study aimed to provide an empirical model of predicting low back pain (LBP) by considering the occupational, personal, and psychological risk factor interactions in workers population employed in industrial units using an artificial neural networks approach.

Authors

Ebrahim Darvishi
Hassan Khotanlou

Department of Computer Engineering, Bu-Ali Sina University, Hamedan, Iran.
Jamshid Khoubi

Environmental Health Research Center, Kurdistan University of Medical Sciences, Sanandaj, Iran.
Omid Giahi

Environmental Health Research Center, Kurdistan University of Medical Sciences, Sanandaj, Iran.
Neda Mahdavi

Department of Ergonomics, School of Public Health and Research Center for Health Sciences, Hamadan University of Medical Sciences, Hamadan, Iran.

Keywords

Adult Case-Control Studies Disability Evaluation Female Humans Industry Iran Life Style Low Back Pain Male Middle Aged Neural Networks, Computer Occupational Diseases Occupational Health Predictive Value of Tests Psychology Risk Factors Severity of Illness Index

External Resources

View on PubMed Access via DOI PubMed (28739018)

Prediction Effects of Personal, Psychosocial, and Occupational Risk Factors on Low Back Pain Severity Using Artificial Neural Networks Approach in Industrial Workers.

Abstract

Authors

Keywords

External Resources

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