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MUST-Plus: A Machine Learning Classifier That Improves Malnutrition Screening in Acute Care Facilities.
Timsina, Prem; Joshi, Himanshu N; Cheng, Fu-Yuan; Kersch, Ilana; Wilson, Sara; Colgan, Claudia; Freeman, Robert; Reich, David L; Mechanick, Jeffrey; Mazumdar, Madhu; Levin, Matthew A; Kia, Arash.
Afiliação
  • Timsina P; Institute for Healthcare Delivery Science, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
  • Joshi HN; Institute for Healthcare Delivery Science, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
  • Cheng FY; Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
  • Kersch I; Institute for Healthcare Delivery Science, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
  • Wilson S; Clinical Nutrition, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
  • Colgan C; Clinical Nutrition, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
  • Freeman R; Hospital Administration, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
  • Reich DL; Institute for Healthcare Delivery Science, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
  • Mechanick J; Hospital Administration, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
  • Mazumdar M; Hospital Administration, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
  • Levin MA; Department of Anesthesiology, Perioperative and Pain Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
  • Kia A; Divisions of Cardiology and Endocrinology, Diabetes and Bone Disease, All at the Icahn School of Medicine at Mount Sinai, NY, New York, USA.
J Am Coll Nutr ; 40(1): 3-12, 2021 01.
Article em En | MEDLINE | ID: mdl-32701397
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Limite: Adult / Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Limite: Adult / Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article