Effect of deep learning-based assistive technology use on chest radiograph interpretation by emergency department physicians: a prospective interventional simulation-based study.

Kim, Ji Hoon; Han, Sang Gil; Cho, Ara; Shin, Hye Jung; Baek, Song-Ee

Kim, Ji Hoon; Han, Sang Gil; Cho, Ara; Shin, Hye Jung; Baek, Song-Ee.

Afiliação

Kim JH; Department of Emergency Medicine, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea.
Han SG; Department of Preventive Medicine , Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea.
Cho A; Department of Emergency Medicine, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea.
Shin HJ; Department of Emergency Medicine, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea.
Baek SE; Department of Research Affairs, Biostatistics Collaboration Unit, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea.

BMC Med Inform Decis Mak ; 21(1): 311, 2021 11 08.

Article em En | MEDLINE | ID: mdl-34749731

Assuntos

Aprendizado Profundo; Médicos; Tecnologia Assistiva; Serviço Hospitalar de Emergência; Humanos; Radiografia Torácica

Palavras-chave

Chest radiograph; Decision-making; Deep learning-based assistive technology; Emergency department

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Médicos / Tecnologia Assistiva / Aprendizado Profundo Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: BMC Med Inform Decis Mak Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Coréia do Sul

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