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The Utility of Machine Learning Models for Predicting Chemical Contaminants in Drinking Water: Promise, Challenges, and Opportunities
PURPOSE OF REVIEW: This review aims to better understand the utility of machine learning algorithms for predicting spatial patterns of contaminants in the United States (U.S.) drinking water. RECENT FINDINGS: We found 27 U.S. drinking water studies in the past ten years that used machine learning al...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer International Publishing
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9883334/ https://www.ncbi.nlm.nih.gov/pubmed/36527604 http://dx.doi.org/10.1007/s40572-022-00389-x |