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An artificial intelligence electrocardiogram analysis for detecting cardiomyopathy in the peripartum period.
Lee, Yeji; Choi, Byungjin; Lee, Min Sung; Jin, Uram; Yoon, Seokyoung; Jo, Yong-Yeon; Kwon, Joon-Myoung.
Afiliação
  • Lee Y; Department of Obstetrics and Gynecology, Gangdong Miz Women's Hospital, Seoul, Republic of Korea.
  • Choi B; Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, Republic of Korea.
  • Lee MS; Medical research team, Medical AI, Seoul, Republic of Korea. Electronic address: lylm@medicalai.com.
  • Jin U; Department of Cardiology, Ajou University School of Medicine, Suwon, Republic of Korea.
  • Yoon S; Ajou University School of Medicine, Department of Obstetrics and Gynecology, Republic of Korea.
  • Jo YY; Medical research team, Medical AI, Seoul, Republic of Korea.
  • Kwon JM; Medical research team, Medical AI, Seoul, Republic of Korea; Department of Emergency Medicine, Mediplex Sejong Hospital, Incheon, Republic of Korea.; Artificial Intelligence and Big Data Research Center, Sejong Medical Research Institute, Bucheon, Republic of Korea.
Int J Cardiol ; 352: 72-77, 2022 Apr 01.
Article em En | MEDLINE | ID: mdl-35122911
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Complicações Cardiovasculares na Gravidez / Cardiomiopatias Idioma: En Ano de publicação: 2022 Tipo de documento: Article
Texto completo
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XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Complicações Cardiovasculares na Gravidez / Cardiomiopatias Idioma: En Ano de publicação: 2022 Tipo de documento: Article