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Can artificial intelligence help identify elder abuse and neglect?
Rosen, Tony; Zhang, Yiye; Bao, Yuhua; Clark, Sunday; Elman, Alyssa; Wen, Katherine; Jeng, Philip; Lachs, Mark S.
Afiliação
  • Rosen T; Department of Emergency Medicine, Weill Cornell Medical College/NewYork-Presbyterian Hospital.
  • Zhang Y; Department of Health Policy & Research, Weill Cornell Medical College.
  • Bao Y; Department of Health Policy & Research, Weill Cornell Medical College.
  • Clark S; Department of Emergency Medicine, Weill Cornell Medical College/NewYork-Presbyterian Hospital.
  • Elman A; Department of Emergency Medicine, Weill Cornell Medical College/NewYork-Presbyterian Hospital.
  • Wen K; Department of Policy Analysis and Management, Cornell University, Ithaca, New York, USA.
  • Jeng P; Department of Health Policy & Research, Weill Cornell Medical College.
  • Lachs MS; Division of Geriatrics and Palliative Care, Weill Cornell Medical College/NewYork-Presbyterian.
J Elder Abuse Negl ; 32(1): 97-103, 2020.
Article em En | MEDLINE | ID: mdl-31713474
ABSTRACT
A health care encounter is a potentially critical opportunity to detect elder abuse and initiate intervention. Unfortunately, health care providers currently very seldom identify elder abuse. Through development of advanced data analytics techniques such as machine learning, artificial intelligence has the potential to dramatically improve elder abuse identification in health care settings.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Abuso de Idosos / Registros Eletrônicos de Saúde Tipo de estudo: Prognostic_studies Limite: Aged / Aged80 / Humans Idioma: En Revista: J Elder Abuse Negl Assunto da revista: GERIATRIA Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Abuso de Idosos / Registros Eletrônicos de Saúde Tipo de estudo: Prognostic_studies Limite: Aged / Aged80 / Humans Idioma: En Revista: J Elder Abuse Negl Assunto da revista: GERIATRIA Ano de publicação: 2020 Tipo de documento: Article