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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2938602 | PMC |
| http://dx.doi.org/10.4103/0970-0358.63936 | DOI Listing |
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Occupational Exposure to Mercury at an Electronics Waste and Lamp Recycling Facility - Ohio, 2023.
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Workers in electronics waste and lamp recycling facilities are at risk of exposure to elemental mercury through inhalation of mercury vapor and mercury-containing dust. Employers at an electronics waste and lamp recycling facility in Ohio that crushes mercury-containing lamps expressed concerns about mercury exposure from work processes and requested a health hazard evaluation by CDC's National Institute for Occupational Safety and Health (NIOSH). In April 2023, NIOSH conducted a multidisciplinary investigation to assess elemental and inorganic mercury exposures, including epidemiologic, environmental, and ventilation assessments.
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Cochrane Database Syst Rev
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Cochrane Denmark and Centre for Evidence-Based Medicine Odense (CEBMO), University of Southern Denmark, Odense, Denmark.
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View Article and Find Full Text PDF[Validity and Reliability of the Korean Version of the Occupational Coping Self-Efficacy Scale for Nurses].
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Department of Nursing, Graduate School, Kunsan National University, Gunsan, Korea.
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Høyskolen Kristiania, Oslo, Norway.
Article Synopsis
- The study compares machine learning approaches to traditional statistical models for survival analysis, specifically in predicting time to return to work for families with complex issues.
- The results show that no model clearly outperformed the others, with both machine learning and classical models displaying low predictive power.
- While machine learning approaches exhibited better fit metrics, particularly the Random Survival Forest, this did not lead to significantly improved predictive accuracy over classical methods, indicating the need for further refinement of these algorithms.
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