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Volume 12 Issue 5
Sep.  2021
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YU Weihong, ZHANG Xiao, WU Chan, CHEN Huan, YANG Zhikun, HE Feng, ZHANG Zhiqiao, ZHANG Bilei, GONG Di, WANG Yuelin, YANG Jingyuan, LI Bing, SUN Yanyuan, MA Yajing, LU Huiqin, XIA Wei, ZHOU Wei, ZHANG Donglei, PAN Qingmin, YANG Ning, WANG Shuna, SUN Xiaolei, YU Ying, SU Chang, WAN Bo, WANG Mingqi, WANG Min, CHEN Youxin. Procedures of Establishing a Well-annotated Database of Color Fundus Photography of Diabetic Retinopathy for Artificial Intelligence Research[J]. Medical Journal of Peking Union Medical College Hospital, 2021, 12(5): 684-688. DOI: 10.12290/xhyxzz.2021-0613
Citation: YU Weihong, ZHANG Xiao, WU Chan, CHEN Huan, YANG Zhikun, HE Feng, ZHANG Zhiqiao, ZHANG Bilei, GONG Di, WANG Yuelin, YANG Jingyuan, LI Bing, SUN Yanyuan, MA Yajing, LU Huiqin, XIA Wei, ZHOU Wei, ZHANG Donglei, PAN Qingmin, YANG Ning, WANG Shuna, SUN Xiaolei, YU Ying, SU Chang, WAN Bo, WANG Mingqi, WANG Min, CHEN Youxin. Procedures of Establishing a Well-annotated Database of Color Fundus Photography of Diabetic Retinopathy for Artificial Intelligence Research[J]. Medical Journal of Peking Union Medical College Hospital, 2021, 12(5): 684-688. DOI: 10.12290/xhyxzz.2021-0613
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Procedures of Establishing a Well-annotated Database of Color Fundus Photography of Diabetic Retinopathy for Artificial Intelligence Research

  • 1.

    Key Laboratory of Ocular Fundus Diseases, Chinese Academy of Medical Sciences; Department of Ophthalmology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China

  • 2.

    Department of Ophthalmology, China-Japan Friendship Hospital, Beijing 100029, China

  • 3.

    Department of Ophthalmology, Xi'an NO.1 Hospital, Xi'an 710002, China

  • 4.

    Department of Ophthalmology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215006, China

  • 5.

    Department of Ophthalmology, Tianjin Medical University General Hospital, Tianjin 300052, China

  • 6.

    Department of Ophthalmology, The First Hospital of Shanxi Medical University, Taiyuan 030001, China

  • 7.

    Department of Ophthalmology, The Second Affiliated Hospital of Shandong First Medical University, Tai'an, Shandong 271016, China

  • 8.

    Department of Ophthalmology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu 221004, China

  • 9.

    Ophthalmology Center, Affiliated Hospital of Weifang Medical College, Weifang, Shandong 261035, China

  • 10.

    Eye Hospital of Shandong First Medical University, Jinan 250021, China

  • 11.

    Department of Ophthalmology, The Forth Hospital of Harbin Medical university, Harbin 150001, China

  • 12.

    Department of Ophthalmology, The Affiliated Hospital of Chengde Medical College, Chengde, Hebei 067020, China

  • 13.

    Department of Ophthalmology, Beijing Luhe Hospital, Capital Medical University, Beijing 101199, China

  • 14.

    Department of Ophthalmology, The First People's Hospital of Pingdingshan, Pingdingshan, Henan 467099, China

  • 15.

    Department of Ophthalmology, The First People's Hospital of Xianyang, Xianyang, Shaanxi 712099, China

Funds: 

The Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences 2018PT32029

CAMS Innovation Fund for Medical Sciences 2018-I2M-AI-001

Pharmaceutical Collaborative Innovation Research Project of Beijing Science and Technology Commission Z191100007719002

Pharmaceutical Collaborative Innovation Research Project of Beijing Science and Technology Commission L192062

Beijing Tianjin Hebei Basic Research Cooperation Project J200006

More Information
  • Corresponding author:

    CHEN Youxin  Tel: 86-10-69156351, E-mail: chenyouxinpumch@163.com

  • Received Date: August 24, 2021
  • Accepted Date: September 05, 2021
  • Available Online: September 14, 2021
  • Issue Publish Date: September 29, 2021
    Graphical Abstract
    • Abstract
  • With the development of artificial intelligence technology, explosive research on the recognition of retina diseases with artificial intelligence was published worldwide, among which, diabetic retinopathy attracted most attention. However, evaluation of different artificial intelligence software remains a problem. The Department of Ophthalmology, Peking Union Medical College Hospital published the first standard well-annotated color photo database of diabetic retinopathy for artificial intelligence research in China. We herein present the procedures for the establishment of the database and aim to provide reference for the future development of similar databases.
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    • References (5)
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    王亚星, 薛灿灿, 李建军. 眼科人工智能研究存在的主要问题及对策[J]. 眼科, 2021, 30: 81-84. https://www.cnki.com.cn/Article/CJFDTOTAL-YAKE202102004.htm
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    U.S. Food and Drug Administration. FDA permits marketing of artificial intelligence-based device to detect certain diabetes-related eye problems[EB/OL]. (2018-04-11)[2021-08-21]. https://www.fda.gov/news-events/press-announcements/fda-permits-marketing-artificial-intelligence-based-device-detect-certain-diabetes-related-eye.
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    Gulshan V, Peng L, Coram M, et al. Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs[J]. JAMA, 2016, 316: 2402-2410. DOI: 10.1001/jama.2016.17216
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