Development and validation of an interpretable machine learning model for predicting hyperuricemia risk: Based on environmental chemical exposure
Hyperuricemia is a global health concern, with environmental chemicals as risk factors. This study used data of multiple environmental chemical exposures from the 2011–2012 cycle of the National Health and Nutrition Examination Survey (NHANES) to develop an interpretable machine learning model for h...
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| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-07-01
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| Series: | Ecotoxicology and Environmental Safety |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0147651325007286 |
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