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Machine learning prediction of groundwater arsenic contamination using water quality parameters in the coastal region of Bangladesh.

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Bibliographic Details
Title: Machine learning prediction of groundwater arsenic contamination using water quality parameters in the coastal region of Bangladesh.
Authors: Ullah F; Department of Environmental Science and Disaster Management, Noakhali Science and Technology University, Noakhali, 3814, Bangladesh., Ismail M; Department of Environmental Science and Disaster Management, Noakhali Science and Technology University, Noakhali, 3814, Bangladesh., Basak JK; Department of Environmental Science and Disaster Management, Noakhali Science and Technology University, Noakhali, 3814, Bangladesh. jk.basak@nstu.edu.bd., Paudel B; Future Regions Research Centre, Ararat Jobs and Technology Precinct, Federation University, Mount Helen, VIC, 3350, Australia., Ahmed S; Department of Environmental Science and Disaster Management, Noakhali Science and Technology University, Noakhali, 3814, Bangladesh., Khan AS; Department of Environmental Science and Disaster Management, Noakhali Science and Technology University, Noakhali, 3814, Bangladesh.
Source: Environmental geochemistry and health [Environ Geochem Health] 2025 Dec 22; Vol. 48 (2), pp. 64. Date of Electronic Publication: 2025 Dec 22.
Publication Type: Journal Article
Journal Info: Publisher: Kluwer Academic Publishers Country of Publication: Netherlands NLM ID: 8903118 Publication Model: Electronic Cited Medium: Internet ISSN: 1573-2983 (Electronic) Linking ISSN: 02694042 NLM ISO Abbreviation: Environ Geochem Health Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1573-2983
DOI:10.1007/s10653-025-02955-2