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Machine Learning Models for Predicting Long-Term Visual Acuity in Highly Myopic Eyes.
Wang, Yining; Du, Ran; Xie, Shiqi; Chen, Changyu; Lu, Hongshuang; Xiong, Jianping; Ting, Daniel S W; Uramoto, Kengo; Kamoi, Koju; Ohno-Matsui, Kyoko.
Afiliación
  • Wang Y; Department of Ophthalmology and Visual Science, Tokyo Medical and Dental University, Tokyo, Japan.
  • Du R; Department of Ophthalmology and Visual Science, Tokyo Medical and Dental University, Tokyo, Japan.
  • Xie S; Department of Ophthalmology, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China.
  • Chen C; Department of Ophthalmology and Visual Science, Tokyo Medical and Dental University, Tokyo, Japan.
  • Lu H; Department of Ophthalmology and Visual Science, Tokyo Medical and Dental University, Tokyo, Japan.
  • Xiong J; Department of Ophthalmology and Visual Science, Tokyo Medical and Dental University, Tokyo, Japan.
  • Ting DSW; Department of Ophthalmology and Visual Science, Tokyo Medical and Dental University, Tokyo, Japan.
  • Uramoto K; Singapore National Eye Center, Singapore Eye Research Institute, Singapore, Singapore.
  • Kamoi K; Duke-NUS Medical School, National University of Singapore, Singapore.
  • Ohno-Matsui K; Department of Ophthalmology and Visual Science, Tokyo Medical and Dental University, Tokyo, Japan.
JAMA Ophthalmol ; 141(12): 1117-1124, 2023 Dec 01.
Article en En | MEDLINE | ID: mdl-37883115

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Enfermedades de la Retina / Baja Visión / Miopía Degenerativa / Degeneración Macular / Miopía Límite: Female / Humans / Middle aged Idioma: En Revista: JAMA Ophthalmol Año: 2023 Tipo del documento: Article País de afiliación: Japón Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Enfermedades de la Retina / Baja Visión / Miopía Degenerativa / Degeneración Macular / Miopía Límite: Female / Humans / Middle aged Idioma: En Revista: JAMA Ophthalmol Año: 2023 Tipo del documento: Article País de afiliación: Japón Pais de publicación: Estados Unidos