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Evaluation of optimal scene time interval for out-of-hospital cardiac arrest using a deep neural network.
Shin, Seung Jae; Bae, Hee Sun; Moon, Hyung Jun; Kim, Gi Woon; Cho, Young Soon; Lee, Dong Wook; Jeong, Dong Kil; Kim, Hyun Joon; Lee, Hyun Jung.
Afiliación
  • Shin SJ; Department of Industrial and System Engineering, Korea Advanced Institute of Science and Technology, Republic of Korea.
  • Bae HS; Department of Industrial and System Engineering, Korea Advanced Institute of Science and Technology, Republic of Korea.
  • Moon HJ; Department of Emergency Medicine, College of Medicine, Soonchunhyang University, Republic of Korea. Electronic address: raintree@schmc.ac.kr.
  • Kim GW; Department of Emergency Medicine, College of Medicine, Soonchunhyang University, Republic of Korea.
  • Cho YS; Department of Emergency Medicine, College of Medicine, Soonchunhyang University, Republic of Korea.
  • Lee DW; Department of Emergency Medicine, College of Medicine, Soonchunhyang University, Republic of Korea.
  • Jeong DK; Department of Emergency Medicine, College of Medicine, Soonchunhyang University, Republic of Korea.
  • Kim HJ; Department of Emergency Medicine, College of Medicine, Soonchunhyang University, Republic of Korea.
  • Lee HJ; Department of Emergency Medicine, College of Medicine, Soonchunhyang University, Republic of Korea.
Am J Emerg Med ; 63: 29-37, 2023 01.
Article en En | MEDLINE | ID: mdl-36544293
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Reanimación Cardiopulmonar / Servicios Médicos de Urgencia / Paro Cardíaco Extrahospitalario Tipo de estudio: Observational_studies / Prognostic_studies Límite: Female / Humans / Male Idioma: En Revista: Am J Emerg Med Año: 2023 Tipo del documento: Article Pais de publicación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Reanimación Cardiopulmonar / Servicios Médicos de Urgencia / Paro Cardíaco Extrahospitalario Tipo de estudio: Observational_studies / Prognostic_studies Límite: Female / Humans / Male Idioma: En Revista: Am J Emerg Med Año: 2023 Tipo del documento: Article Pais de publicación: Estados Unidos