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

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

Assuntos

Inteligência Artificial; Abuso de Idosos/diagnóstico; Registros Eletrônicos de Saúde; Idoso; Idoso de 80 Anos ou mais; Pessoal de Saúde; Humanos

Palavras-chave

Elder abuse; electronic health records; insurance claims; machine learning

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Texto completo: 1 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

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