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Progress of artificial intelligence in diabetic retinopathy screening.
Wang, Yue-Lin; Yang, Jing-Yun; Yang, Jing-Yuan; Zhao, Xin-Yu; Chen, You-Xin; Yu, Wei-Hong.
Afiliación
  • Wang YL; Department of Ophthalmology, Peking Union Medical College Hospital & Chinese Academy of Medical Sciences, Beijing, China.
  • Yang JY; Key Laboratory of Ocular Fundus Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
  • Yang JY; Division of Statistics, School of Economics & Research Center of Financial Information, Shanghai University, Shanghai, China.
  • Zhao XY; Rush Alzheimer's Disease Center & Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois, USA.
  • Chen YX; Department of Ophthalmology, Peking Union Medical College Hospital & Chinese Academy of Medical Sciences, Beijing, China.
  • Yu WH; Key Laboratory of Ocular Fundus Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Diabetes Metab Res Rev ; 37(5): e3414, 2021 07.
Article en En | MEDLINE | ID: mdl-33010796
Diabetic retinopathy (DR) is one of the leading causes of blindness worldwide, and the limited availability of qualified ophthalmologists restricts its early diagnosis. For the past few years, artificial intelligence technology has developed rapidly and has been applied in DR screening. The upcoming technology provides support on DR screening and improves the identification of DR lesions with a high sensitivity and specificity. This review aims to summarize the progress on automatic detection and classification models for the diagnosis of DR.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Retinopatía Diabética Tipo de estudio: Diagnostic_studies / Prognostic_studies / Screening_studies Límite: Humans Idioma: En Revista: Diabetes Metab Res Rev Asunto de la revista: ENDOCRINOLOGIA / METABOLISMO Año: 2021 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Retinopatía Diabética Tipo de estudio: Diagnostic_studies / Prognostic_studies / Screening_studies Límite: Humans Idioma: En Revista: Diabetes Metab Res Rev Asunto de la revista: ENDOCRINOLOGIA / METABOLISMO Año: 2021 Tipo del documento: Article País de afiliación: China