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A fundus image dataset for intelligent retinopathy of prematurity system.
Zhao, Xinyu; Chen, Shaobin; Zhang, Sifan; Liu, Yaling; Hu, Yarou; Yuan, Duo; Xie, Liqiong; Luo, Xiayuan; Zheng, Mianying; Tian, Ruyin; Chen, Yi; Tan, Tao; Yu, Zhen; Sun, Yue; Wu, Zhenquan; Zhang, Guoming.
Afiliación
  • Zhao X; Shenzhen Eye Hospital, Jinan University, Shenzhen Eye Institute, Shenzhen, China.
  • Chen S; Faculty of Applied Sciences, Macao Polytechnic University, Macao Special Administrative Region of China, Macao, China.
  • Zhang S; Department of Biology, New York University, New York, NY, US.
  • Liu Y; Shenzhen Eye Hospital, Jinan University, Shenzhen Eye Institute, Shenzhen, China.
  • Hu Y; Shenzhen Eye Hospital, Jinan University, Shenzhen Eye Institute, Shenzhen, China.
  • Yuan D; Shenzhen Eye Hospital, Jinan University, Shenzhen Eye Institute, Shenzhen, China.
  • Xie L; State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, 510060, China.
  • Luo X; Shenzhen Eye Hospital, Jinan University, Shenzhen Eye Institute, Shenzhen, China.
  • Zheng M; Shenzhen Eye Hospital, Jinan University, Shenzhen Eye Institute, Shenzhen, China.
  • Tian R; Shenzhen Eye Hospital, Jinan University, Shenzhen Eye Institute, Shenzhen, China.
  • Chen Y; Shenzhen Eye Hospital, Jinan University, Shenzhen Eye Institute, Shenzhen, China.
  • Tan T; Faculty of Applied Sciences, Macao Polytechnic University, Macao Special Administrative Region of China, Macao, China.
  • Yu Z; Shenzhen Eye Hospital, Jinan University, Shenzhen Eye Institute, Shenzhen, China.
  • Sun Y; Faculty of Applied Sciences, Macao Polytechnic University, Macao Special Administrative Region of China, Macao, China. yuesun@mpu.edu.mo.
  • Wu Z; Shenzhen Eye Hospital, Jinan University, Shenzhen Eye Institute, Shenzhen, China. wuzhenquan@sz-eyes.com.
  • Zhang G; Shenzhen Eye Hospital, Jinan University, Shenzhen Eye Institute, Shenzhen, China. zhangguoming@sz-eyes.com.
Sci Data ; 11(1): 543, 2024 May 27.
Article en En | MEDLINE | ID: mdl-38802420
ABSTRACT
Image-based artificial intelligence (AI) systems stand as the major modality for evaluating ophthalmic conditions. However, most of the currently available AI systems are designed for experimental research using single-central datasets. Most of them fell short of application in real-world clinical settings. In this study, we collected a dataset of 1,099 fundus images in both normal and pathologic eyes from 483 premature infants for intelligent retinopathy of prematurity (ROP) system development and validation. Dataset diversity was visualized with a spatial scatter plot. Image classification was conducted by three annotators. To the best of our knowledge, this is one of the largest fundus datasets on ROP, and we believe it is conducive to the real-world application of AI systems.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Retinopatía de la Prematuridad / Recien Nacido Prematuro / Inteligencia Artificial / Fondo de Ojo Límite: Humans / Newborn Idioma: En Revista: Sci Data Año: 2024 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Retinopatía de la Prematuridad / Recien Nacido Prematuro / Inteligencia Artificial / Fondo de Ojo Límite: Humans / Newborn Idioma: En Revista: Sci Data Año: 2024 Tipo del documento: Article País de afiliación: China
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