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Application of natural language processing to identify social needs from patient medical notes: development and assessment of a scalable, performant, and rule-based model in an integrated healthcare delivery system.
Gray, Geoffrey M; Zirikly, Ayah; Ahumada, Luis M; Rouhizadeh, Masoud; Richards, Thomas; Kitchen, Christopher; Foroughmand, Iman; Hatef, Elham.
Afiliação
  • Gray GM; Center for Pediatric Data Science and Analytic Methodology, Johns Hopkins All Children's Hospital, St. Petersburg, FL, United States.
  • Zirikly A; Department of Computer Science, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States.
  • Ahumada LM; Center for Pediatric Data Science and Analytic Methodology, Johns Hopkins All Children's Hospital, St. Petersburg, FL, United States.
  • Rouhizadeh M; Department of Pharmaceutical Outcomes and Policy, University of Florida College of Pharmacy, Gainesville, FL, United States.
  • Richards T; Department of Health Policy and Management, Center for Population Health Information Technology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.
  • Kitchen C; Department of Health Policy and Management, Center for Population Health Information Technology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.
  • Foroughmand I; Department of Health Policy and Management, Center for Population Health Information Technology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.
  • Hatef E; Department of Health Policy and Management, Center for Population Health Information Technology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.
JAMIA Open ; 6(4): ooad085, 2023 Dec.
Article em En | MEDLINE | ID: mdl-37799347
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos
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: Estados Unidos