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Prediction of systemic biomarkers from retinal photographs: development and validation of deep-learning algorithms.
Rim, Tyler Hyungtaek; Lee, Geunyoung; Kim, Youngnam; Tham, Yih-Chung; Lee, Chan Joo; Baik, Su Jung; Kim, Young Ah; Yu, Marco; Deshmukh, Mihir; Lee, Byoung Kwon; Park, Sungha; Kim, Hyeon Chang; Sabayanagam, Charumathi; Ting, Daniel S W; Wang, Ya Xing; Jonas, Jost B; Kim, Sung Soo; Wong, Tien Yin; Cheng, Ching-Yu.
Afiliación
  • Rim TH; Singapore Eye Research Institute, Singapore National Eye Centre, Singapore; Ophthalmology and Visual Sciences Academic Clinical Program, Duke-NUS Medical School, Singapore; Department of Ophthalmology, Institute of Vision Research, Severance Hospital, Yonsei University College of Medicine, Seoul, So
  • Lee G; Medi Whale, Seoul, South Korea.
  • Kim Y; Medi Whale, Seoul, South Korea.
  • Tham YC; Singapore Eye Research Institute, Singapore National Eye Centre, Singapore; Ophthalmology and Visual Sciences Academic Clinical Program, Duke-NUS Medical School, Singapore.
  • Lee CJ; Division of Cardiology, Severance Cardiovascular Hospital, Yonsei University College of Medicine, Seoul, South Korea.
  • Baik SJ; Healthcare Research Team, Health Promotion Center, Severance Gangnam Hospital, Yonsei University College of Medicine, Seoul, South Korea.
  • Kim YA; Division of Medical Information and Technology, Yonsei University College of Medicine, Seoul, South Korea.
  • Yu M; Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.
  • Deshmukh M; Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.
  • Lee BK; Division of Cardiology, Severance Gangnam Hospital, Yonsei University College of Medicine, Seoul, South Korea.
  • Park S; Division of Cardiology, Severance Cardiovascular Hospital, Yonsei University College of Medicine, Seoul, South Korea; Integrated Research Center for Cerebrovascular and Cardiovascular Disease, Yonsei University College of Medicine, Seoul, South Korea.
  • Kim HC; Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, South Korea.
  • Sabayanagam C; Singapore Eye Research Institute, Singapore National Eye Centre, Singapore; Ophthalmology and Visual Sciences Academic Clinical Program, Duke-NUS Medical School, Singapore.
  • Ting DSW; Singapore Eye Research Institute, Singapore National Eye Centre, Singapore; Ophthalmology and Visual Sciences Academic Clinical Program, Duke-NUS Medical School, Singapore.
  • Wang YX; Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, China.
  • Jonas JB; Department of Ophthalmology, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
  • Kim SS; Department of Ophthalmology, Institute of Vision Research, Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea. Electronic address: semekim@yuhs.ac.
  • Wong TY; Singapore Eye Research Institute, Singapore National Eye Centre, Singapore; Ophthalmology and Visual Sciences Academic Clinical Program, Duke-NUS Medical School, Singapore.
  • Cheng CY; Singapore Eye Research Institute, Singapore National Eye Centre, Singapore; Ophthalmology and Visual Sciences Academic Clinical Program, Duke-NUS Medical School, Singapore. Electronic address: chingyu.cheng@duke-nus.edu.sg.
Lancet Digit Health ; 2(10): e526-e536, 2020 10.
Article en En | MEDLINE | ID: mdl-33328047
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Retina / Composición Corporal / Algoritmos / Procesamiento de Imagen Asistido por Computador / Creatinina / Aprendizaje Profundo / Modelos Biológicos Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Female / Humans / Male / Middle aged País/Región como asunto: Asia / Europa Idioma: En Revista: Lancet Digit Health Año: 2020 Tipo del documento: Article País de afiliación: Somalia Pais de publicación: Reino Unido
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Retina / Composición Corporal / Algoritmos / Procesamiento de Imagen Asistido por Computador / Creatinina / Aprendizaje Profundo / Modelos Biológicos Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Female / Humans / Male / Middle aged País/Región como asunto: Asia / Europa Idioma: En Revista: Lancet Digit Health Año: 2020 Tipo del documento: Article País de afiliación: Somalia Pais de publicación: Reino Unido