AIMC Topic: Miners

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Early warning of deep coal miners' unsafe behavior based on the HFACS-CM-BP neural network.

International journal of occupational safety and ergonomics : JOSE Mar 26, 2025
Preventing miners' unsafe behavior and reducing accidents in deep coal mines are crucial. This study comprehensively used methods such as the human factor analysis and classification system for China mines (HFACS-CM) model, grounded theory and the ba...
Humans Neural Networks, Computer China Accidents, Occupational Safety Management Occupational Health Coal Mining Grounded Theory Miners
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Web application using machine learning to predict cardiovascular disease and hypertension in mine workers.

Scientific reports Dec 30, 2024
This study presents a web application for predicting cardiovascular disease (CVD) and hypertension (HTN) among mine workers using machine learning (ML) techniques. The dataset, collected from 699 participants at the Gol-Gohar mine in Iran between 201...
Humans Machine Learning Female Risk Factors Adult Male Cardiovascular Diseases Middle Aged Risk Assessment Hypertension Internet Iran Occupational Health Mining Occupational Diseases Miners
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[Neural network analysis of mechanization's impact on coal miner's occupational health].

Zhonghua lao dong wei sheng zhi ye bing za zhi = Zhonghua laodong weisheng zhiyebing zazhi = Chinese journal of industrial hygiene and occupational diseases May 20, 2024
In order to clarify the transmission mechanism of the impact of mechanization on the occupational health of miners and to provide empirical evidence for the development of new quality productivity in the coal industry that balances health and efficie...
Humans Neural Networks, Computer Surveys and Questionnaires Bayes Theorem Occupational Health Occupational Diseases Coal Mining Miners
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