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Prediction of postpartum prediabetes by machine learning methods in women with gestational diabetes mellitus.
Parkhi, Durga; Periyathambi, Nishanthi; Ghebremichael-Weldeselassie, Yonas; Patel, Vinod; Sukumar, Nithya; Siddharthan, Rahul; Narlikar, Leelavati; Saravanan, Ponnusamy.
Afiliação
  • Parkhi D; Populations, Evidence, and Technologies, Division of Health Sciences, University of Warwick, Coventry, UK.
  • Periyathambi N; Populations, Evidence, and Technologies, Division of Health Sciences, University of Warwick, Coventry, UK.
  • Ghebremichael-Weldeselassie Y; Department of Diabetes, Endocrinology, and Metabolism, George Eliot Hospital, Nuneaton, UK.
  • Patel V; Populations, Evidence, and Technologies, Division of Health Sciences, University of Warwick, Coventry, UK.
  • Sukumar N; School of Mathematics and Statistics, The Open University, Milton Keynes, UK.
  • Siddharthan R; Department of Diabetes, Endocrinology, and Metabolism, George Eliot Hospital, Nuneaton, UK.
  • Narlikar L; Populations, Evidence, and Technologies, Division of Health Sciences, University of Warwick, Coventry, UK.
  • Saravanan P; Department of Diabetes, Endocrinology, and Metabolism, George Eliot Hospital, Nuneaton, UK.
iScience ; 26(10): 107846, 2023 Oct 20.
Article em En | MEDLINE | ID: mdl-37767000
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Reino Unido
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Reino Unido