AIMC Topic: Occupational Diseases
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PEDF, a pleiotropic WTC-LI biomarker: Machine learning biomarker identification and validation.
PLoS computational biology
Jul 21, 2021
Biomarkers predict World Trade Center-Lung Injury (WTC-LI); however, there remains unaddressed multicollinearity in our serum cytokines, chemokines, and high-throughput platform datasets used to phenotype WTC-disease. To address this concern, we used...
A novel vision-based real-time method for evaluating postural risk factors associated with musculoskeletal disorders.
Applied ergonomics
May 4, 2020
Real-time risk assessment for work-related musculoskeletal disorders (MSD) has been a challenging research problem. Previous methods such as using depth cameras suffered from limited visual range and wearable sensors could cause intrusiveness to the ...
Measuring Biomechanical Risk in Lifting Load Tasks Through Wearable System and Machine-Learning Approach.
Sensors (Basel, Switzerland)
Mar 11, 2020
Ergonomics evaluation through measurements of biomechanical parameters in real time has a great potential in reducing non-fatal occupational injuries, such as work-related musculoskeletal disorders. Assuming a correct posture guarantees the avoidance...
A machine learning approach to detect changes in gait parameters following a fatiguing occupational task.
Ergonomics
Mar 2, 2018
The purpose of this study is to provide a method for classifying non-fatigued vs. fatigued states following manual material handling. A method of template matching pattern recognition for feature extraction ($1 Recognizer) along with the support vect...
Prediction Effects of Personal, Psychosocial, and Occupational Risk Factors on Low Back Pain Severity Using Artificial Neural Networks Approach in Industrial Workers.
Journal of manipulative and physiological therapeutics
Jul 21, 2017
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 ...
Experimental evaluation of a novel robotic hospital bed mover with omni-directional mobility.
Applied ergonomics
May 6, 2017
Bed pushing during patient transfer is one of the most physically demanding and yet common tasks in the hospital setting. Powered bed movers have been increasingly introduced to hospitals to reduce physiological strains on the users. This study intro...
Prediction of hearing loss among the noise-exposed workers in a steel factory using artificial intelligence approach.
International archives of occupational and environmental health
Nov 29, 2014
PURPOSE: Prediction of hearing loss in noisy workplaces is considered to be an important aspect of hearing conservation program. Artificial intelligence, as a new approach, can be used to predict the complex phenomenon such as hearing loss. Using art...
Comparison of postural ergonomics between laparoscopic and robotic sacrocolpopexy: a pilot study.
Journal of minimally invasive gynecology
Oct 12, 2014
STUDY OBJECTIVE: To compare resident, fellow, and attending urologic and gynecologic surgeons' musculoskeletal and mental strain during laparoscopic and robotic sacrocolpopexy.
Metabolomic machine learning predictor for arsenic-associated hypertension risk in male workers.
Journal of pharmaceutical and biomedical analysis
Jul 15, 2025
Arsenic (As)-induced hypertension is a significant public health concern, highlighting the need for early risk prediction. This study aimed to develop a predictive model for occupational As exposure and hypertension using metabolomics and machine lea...
Predicting Pneumoconiosis Risk in Coal Workers using Artificial Neural Networks.
Puerto Rico health sciences journal
Jun 1, 2025
OBJECTIVE: This study aimed to create a model to predict pneumoconiosis risk in coal workers using artificial neural networks (ANNs).
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