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A deep learning algorithm to detect anaemia with ECGs: a retrospective, multicentre study.
Kwon, Joon-Myoung; Cho, Younghoon; Jeon, Ki-Hyun; Cho, Soohyun; Kim, Kyung-Hee; Baek, Seung Don; Jeung, Soomin; Park, Jinsik; Oh, Byung-Hee.
Afiliação
  • Kwon JM; Department of Emergency Medicine, Mediplex Sejong Hospital, Incheon, South Korea; Artificial Intelligence and Big Data Research Center, Sejong Medical Research Institute, Bucheon, South Korea; Medical research team, Medical AI, Seoul, South Korea.
  • Cho Y; Medical Research and Development Center, Bodyfriend, Seoul, South Korea.
  • Jeon KH; Division of Cardiology, Cardiovascular Center, Mediplex Sejong Hospital, Incheon, South Korea; Artificial Intelligence and Big Data Research Center, Sejong Medical Research Institute, Bucheon, South Korea. Electronic address: imcardio@gmail.com.
  • Cho S; Medical Research and Development Center, Bodyfriend, Seoul, South Korea.
  • Kim KH; Division of Cardiology, Cardiovascular Center, Mediplex Sejong Hospital, Incheon, South Korea; Artificial Intelligence and Big Data Research Center, Sejong Medical Research Institute, Bucheon, South Korea.
  • Baek SD; Division of Nephrology, Department of Internal Medicine, Mediplex Sejong Hospital, Incheon, South Korea.
  • Jeung S; Division of Nephrology, Department of Internal Medicine, Mediplex Sejong Hospital, Incheon, South Korea.
  • Park J; Division of Cardiology, Cardiovascular Center, Mediplex Sejong Hospital, Incheon, South Korea; Medical research team, Medical AI, Seoul, South Korea.
  • Oh BH; Division of Cardiology, Cardiovascular Center, Mediplex Sejong Hospital, Incheon, South Korea.
Lancet Digit Health ; 2(7): e358-e367, 2020 07.
Article em En | MEDLINE | ID: mdl-33328095
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Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Eletrocardiografia / Aprendizado Profundo / Anemia Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Aged / Female / Humans / Male / Middle aged País/Região como assunto: Asia Idioma: En Revista: Lancet Digit Health Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Coréia do Sul
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Eletrocardiografia / Aprendizado Profundo / Anemia Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Aged / Female / Humans / Male / Middle aged País/Região como assunto: Asia Idioma: En Revista: Lancet Digit Health Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Coréia do Sul