Deep Learning With Electronic Health Records for Short-Term Fracture Risk Identification: Crystal Bone Algorithm Development and Validation.

Almog, Yasmeen Adar; Rai, Angshu; Zhang, Patrick; Moulaison, Amanda; Powell, Ross; Mishra, Anirban; Weinberg, Kerry; Hamilton, Celeste; Oates, Mary; McCloskey, Eugene; Cummings, Steven R

Almog, Yasmeen Adar; Rai, Angshu; Zhang, Patrick; Moulaison, Amanda; Powell, Ross; Mishra, Anirban; Weinberg, Kerry; Hamilton, Celeste; Oates, Mary; McCloskey, Eugene; Cummings, Steven R.

Afiliação

Almog YA; Digital Health & Innovation, Amgen Inc, Thousand Oaks, CA, United States.
Rai A; Digital Health & Innovation, Amgen Inc, Thousand Oaks, CA, United States.
Zhang P; Digital Health & Innovation, Amgen Inc, Thousand Oaks, CA, United States.
Moulaison A; Digital Health & Innovation, Amgen Inc, Thousand Oaks, CA, United States.
Powell R; Digital Health & Innovation, Amgen Inc, Thousand Oaks, CA, United States.
Mishra A; Digital Health & Innovation, Amgen Inc, Thousand Oaks, CA, United States.
Weinberg K; Digital Health & Innovation, Amgen Inc, Thousand Oaks, CA, United States.
Hamilton C; Global Medical Operations, Amgen Inc, Thousand Oaks, CA, United States.
Oates M; US Medical, Amgen Inc, Thousand Oaks, CA, United States.
McCloskey E; Department of Oncology & Metabolism, The University of Sheffield, Sheffield, United Kingdom.
Cummings SR; Department of Medicine, University of California San Francisco, San Francisco, CA, United States.

J Med Internet Res ; 22(10): e22550, 2020 10 16.

Article em En | MEDLINE | ID: mdl-32956069

Assuntos

Aprendizado Profundo/normas; Registros Eletrônicos de Saúde/normas; Fraturas Ósseas/epidemiologia; Algoritmos; Feminino; Humanos; Masculino; Pessoa de Meia-Idade; Reprodutibilidade dos Testes; Estudos Retrospectivos; Fatores de Risco

Palavras-chave

AI; EHR; NLP; artificial intelligence; bone; deep learning; electronic health record; fracture; low bone mass; machine learning; natural language processing; osteoporosis; prediction

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Contexto em Saúde: 1_ASSA2030 Problema de saúde: 1_sistemas_informacao_saude Assunto principal: Fraturas Ósseas / Registros Eletrônicos de Saúde / Aprendizado Profundo Tipo de estudo: Diagnostic_studies / Etiology_studies / Guideline / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans / Male / Middle aged Idioma: En Revista: J Med Internet Res Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos

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