Research progress in artificial intelligence assisted diabetic retinopathy diagnosis.

Liu, Yun-Fang; Ji, Yu-Ke; Fei, Fang-Qin; Chen, Nai-Mei; Zhu, Zhen-Tao; Fei, Xing-Zhen

Liu, Yun-Fang; Ji, Yu-Ke; Fei, Fang-Qin; Chen, Nai-Mei; Zhu, Zhen-Tao; Fei, Xing-Zhen.

Afiliación

Liu YF; Department of Ophthalmology, First People's Hospital of Huzhou, Huzhou University, Huzhou 313000, Zhejiang Province, China.
Ji YK; Eye Hospital, Nanjing Medical University, Nanjing 210000, Jiangsu Province, China.
Fei FQ; Department of Endocrinology, First People's Hospital of Huzhou, Huzhou University, Huzhou 313000, Zhejiang Province, China.
Chen NM; Department of Ophthalmology, Huai'an Hospital of Huai'an City, Huai'an 223000, Jiangsu Province, China.
Zhu ZT; Department of Ophthalmology, Huai'an Hospital of Huai'an City, Huai'an 223000, Jiangsu Province, China.
Fei XZ; Department of Endocrinology, First People's Hospital of Huzhou, Huzhou University, Huzhou 313000, Zhejiang Province, China.

Int J Ophthalmol ; 16(9): 1395-1405, 2023.

Article en En | MEDLINE | ID: mdl-37724288

Palabras clave

artificial intelligence; deep learning; diabetic retinopathy; diagnosis; grading; lesions segmentation; machine learning

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Screening_studies Idioma: En Revista: Int J Ophthalmol Año: 2023 Tipo del documento: Article País de afiliación: China

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