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Machine learning in understanding environmental variability of vibriosis in coastal waters.

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Title: Machine learning in understanding environmental variability of vibriosis in coastal waters.
Authors: Magers BM; Geohealth and Hydrology Laboratory, Department of Environmental Engineering Sciences, University of Florida, Gainesville, Florida, USA., Brumfield KD; Maryland Pathogen Research Institute, University of Maryland, College Park, Maryland, USA.; University of Maryland Institute for Advanced Computer Studies, University of Maryland, College Park, Maryland, USA., Kumar S; Geohealth and Hydrology Laboratory, Department of Environmental Engineering Sciences, University of Florida, Gainesville, Florida, USA., Colwell RR; Maryland Pathogen Research Institute, University of Maryland, College Park, Maryland, USA.; University of Maryland Institute for Advanced Computer Studies, University of Maryland, College Park, Maryland, USA., Jutla AS; Geohealth and Hydrology Laboratory, Department of Environmental Engineering Sciences, University of Florida, Gainesville, Florida, USA.
Source: Applied and environmental microbiology [Appl Environ Microbiol] 2025 Sep 17; Vol. 91 (9), pp. e0071625. Date of Electronic Publication: 2025 Aug 14.
Publication Type: Journal Article; Research Support, U.S. Gov't, Non-P.H.S.
Journal Info: Publisher: American Society for Microbiology Country of Publication: United States NLM ID: 7605801 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1098-5336 (Electronic) Linking ISSN: 00992240 NLM ISO Abbreviation: Appl Environ Microbiol Subsets: MEDLINE
Database: MEDLINE Ultimate
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PubType: Academic Journal
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  Data: Machine learning in understanding environmental variability of vibriosis in coastal waters.
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  Data: <searchLink fieldCode="AU" term="%22Magers+BM%22">Magers BM</searchLink>; Geohealth and Hydrology Laboratory, Department of Environmental Engineering Sciences, University of Florida, Gainesville, Florida, USA.<br /><searchLink fieldCode="AU" term="%22Brumfield+KD%22">Brumfield KD</searchLink>; Maryland Pathogen Research Institute, University of Maryland, College Park, Maryland, USA.; University of Maryland Institute for Advanced Computer Studies, University of Maryland, College Park, Maryland, USA.<br /><searchLink fieldCode="AU" term="%22Kumar+S%22">Kumar S</searchLink>; Geohealth and Hydrology Laboratory, Department of Environmental Engineering Sciences, University of Florida, Gainesville, Florida, USA.<br /><searchLink fieldCode="AU" term="%22Colwell+RR%22">Colwell RR</searchLink>; Maryland Pathogen Research Institute, University of Maryland, College Park, Maryland, USA.; University of Maryland Institute for Advanced Computer Studies, University of Maryland, College Park, Maryland, USA.<br /><searchLink fieldCode="AU" term="%22Jutla+AS%22">Jutla AS</searchLink>; Geohealth and Hydrology Laboratory, Department of Environmental Engineering Sciences, University of Florida, Gainesville, Florida, USA.
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  Data: <searchLink fieldCode="JN" term="%227605801%22">Applied and environmental microbiology</searchLink> [Appl Environ Microbiol] 2025 Sep 17; Vol. 91 (9), pp. e0071625. <i>Date of Electronic Publication: </i>2025 Aug 14.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22American+Society+for+Microbiology%22">American Society for Microbiology </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>7605801 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1098-5336 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2200992240%22">00992240 </searchLink><i>NLM ISO Abbreviation: </i>Appl Environ Microbiol <i>Subsets: </i>MEDLINE
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        Value: 10.1128/aem.00716-25
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      – Code: eng
        Text: English
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              Text: 2025 Sep 17
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