Machine learning to predict foodborne salmonellosis outbreaks based on genome characteristics and meteorological trends.

Karanth, Shraddha; Patel, Jitendra; Shirmohammadi, Adel; Pradhan, Abani K

Karanth, Shraddha; Patel, Jitendra; Shirmohammadi, Adel; Pradhan, Abani K.

Afiliação

Karanth S; Department of Nutrition and Food Science, University of Maryland, College Park, MD, 20742, USA.
Patel J; Environmental Microbial & Food Safety Lab, USDA-ARS, Beltsville, MD, 20705, USA.
Shirmohammadi A; Environmental Science & Technology, University of Maryland, College Park, MD, 20742, USA.
Pradhan AK; Department of Nutrition and Food Science, University of Maryland, College Park, MD, 20742, USA.

Curr Res Food Sci ; 6: 100525, 2023.

Article em En | MEDLINE | ID: mdl-37377491

Palavras-chave

Elastic net; Meteorological variables; Outbreaks; Salmonellosis; Whole genome sequencing

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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Curr Res Food Sci Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos

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