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Harnessing machine learning models for non-invasive pre-diabetes screening in children and adolescents.
Kushwaha, Savitesh; Srivastava, Rachana; Jain, Rachita; Sagar, Vivek; Aggarwal, Arun Kumar; Bhadada, Sanjay Kumar; Khanna, Poonam.
Afiliação
  • Kushwaha S; Department of Community Medicine and School of Public Health, Postgraduate Institute of Medical Education and Research, Chandigarh 160012, India.
  • Srivastava R; Department of Community Medicine and School of Public Health, Postgraduate Institute of Medical Education and Research, Chandigarh 160012, India.
  • Jain R; Department of Community Medicine and School of Public Health, Postgraduate Institute of Medical Education and Research, Chandigarh 160012, India.
  • Sagar V; Department of Community Medicine and School of Public Health, Postgraduate Institute of Medical Education and Research, Chandigarh 160012, India.
  • Aggarwal AK; Department of Community Medicine and School of Public Health, Postgraduate Institute of Medical Education and Research, Chandigarh 160012, India.
  • Bhadada SK; Department of Endocrinology, Postgraduate Institute of Medical Education and Research, Chandigarh 160012, India.
  • Khanna P; Department of Community Medicine and School of Public Health, Postgraduate Institute of Medical Education and Research, Chandigarh 160012, India. Electronic address: poonamkhanna05@gmail.com.
Comput Methods Programs Biomed ; 226: 107180, 2022 Nov.
Article em En | MEDLINE | ID: mdl-36279639
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Estado Pré-Diabético / Diabetes Mellitus Tipo de estudo: Diagnostic_studies / Prognostic_studies / Screening_studies Limite: Adolescent / Child / Humans Idioma: En Revista: Comput Methods Programs Biomed Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Índia País de publicação: Irlanda
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Estado Pré-Diabético / Diabetes Mellitus Tipo de estudo: Diagnostic_studies / Prognostic_studies / Screening_studies Limite: Adolescent / Child / Humans Idioma: En Revista: Comput Methods Programs Biomed Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Índia País de publicação: Irlanda