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Analyzing the Impact of Occupational Exposures on Male Fertility Indicators: A Machine Learning Approach

Research RF Safe Research Library Jan 1, 2025

This occupational epidemiology study used machine learning to evaluate whether workplace exposures (including magnetic and electric fields, vibration, noise, and heat stress) predict male reproductive indicators in 80 workers. The models and explainable AI outputs highlighted magnetic and electric field exposures and age as key predictors linked to lower free testosterone. The authors also report a 10-year forecast identifying electric field exposure as the most important long-term risk factor.

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