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A deep learning system for myopia onset prediction and intervention effectiveness evaluation in children.
Qi, Ziyi; Li, Tingyao; Chen, Jun; Yam, Jason C; Wen, Yang; Huang, Gengyou; Zhong, Hua; He, Mingguang; Zhu, Dan; Dai, Rongping; Qian, Bo; Wang, Jingjing; Qian, Chaoxu; Wang, Wei; Zheng, Yanfei; Zhang, Jian; Yi, Xianglong; Wang, Zheyuan; Zhang, Bo; Liu, Chunyu; Cheng, Tianyu; Yang, Xiaokang; Li, Jun; Pan, Yan-Ting; Ding, Xiaohu; Xiong, Ruilin; Wang, Yan; Zhou, Yan; Feng, Dagan; Liu, Sichen; Du, Linlin; Yang, Jinliuxing; Zhu, Zhuoting; Bi, Lei; Kim, Jinman; Tang, Fangyao; Zhang, Yuzhou; Zhang, Xiujuan; Zou, Haidong; Ang, Marcus; Tham, Clement C; Cheung, Carol Y; Pang, Chi Pui; Sheng, Bin; He, Xiangui; Xu, Xun.
Affiliation
  • Qi Z; Department of Clinical Research, Shanghai Eye Disease Prevention and Treatment Center, Shanghai Eye Hospital, Shanghai Vision Health Center & Shanghai Children Myopia Institute, Shanghai, China.
  • Li T; Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, National Clinical Research Center for Eye Diseases, Center of Eye Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai Engineering Center for Visual Science and Photomedicine, Shanghai, C
  • Chen J; Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China.
  • Yam JC; MOE Key Laboratory of AI, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China.
  • Wen Y; Department of Clinical Research, Shanghai Eye Disease Prevention and Treatment Center, Shanghai Eye Hospital, Shanghai Vision Health Center & Shanghai Children Myopia Institute, Shanghai, China.
  • Huang G; Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Kowloon, Hong Kong.
  • Zhong H; Guangdong Provincial Key Laboratory of Intelligent Information Processing, College of Electronic and Information Engineering, Shenzhen University, Shenzhen, China.
  • He M; Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China.
  • Zhu D; MOE Key Laboratory of AI, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China.
  • Dai R; Department of Ophthalmology, First Affiliated Hospital of Kunming Medical University, Kunming, China.
  • Qian B; Experimental Ophthalmology, The Hong Kong Polytechnic University, Kowloon, Hong Kong.
  • Wang J; State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China.
  • Qian C; Department of Ophthalmology, The Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia, China.
  • Wang W; Department of Ophthalmology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
  • Zheng Y; Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China.
  • Zhang J; MOE Key Laboratory of AI, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China.
  • Yi X; Department of Clinical Research, Shanghai Eye Disease Prevention and Treatment Center, Shanghai Eye Hospital, Shanghai Vision Health Center & Shanghai Children Myopia Institute, Shanghai, China.
  • Wang Z; Department of Ophthalmology, First Affiliated Hospital of Kunming Medical University, Kunming, China.
  • Zhang B; State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China.
  • Liu C; Department of Ophthalmology, The Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia, China.
  • Cheng T; Department of Ophthalmology, Beijing Friendship Hospital Pinggu Campus, Capital Medical University, Beijing, China.
  • Yang X; Department of Ophthalmology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, China.
  • Li J; Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China.
  • Pan YT; MOE Key Laboratory of AI, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China.
  • Ding X; Department of Clinical Research, Shanghai Eye Disease Prevention and Treatment Center, Shanghai Eye Hospital, Shanghai Vision Health Center & Shanghai Children Myopia Institute, Shanghai, China.
  • Xiong R; Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China.
  • Wang Y; MOE Key Laboratory of AI, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China.
  • Zhou Y; Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, National Clinical Research Center for Eye Diseases, Center of Eye Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai Engineering Center for Visual Science and Photomedicine, Shanghai, C
  • Feng D; MOE Key Laboratory of AI, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China.
  • Liu S; Affiliated Hospital of Yunnan University, Kunming, China.
  • Du L; Affiliated Hospital of Yunnan University, Kunming, China.
  • Yang J; State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China.
  • Zhu Z; State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China.
  • Bi L; Department of Ophthalmology, The Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia, China.
  • Kim J; Department of Ophthalmology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
  • Tang F; School of Computer Science, The University of Sydney, Sydney, NSW, Australia.
  • Zhang Y; Department of Clinical Research, Shanghai Eye Disease Prevention and Treatment Center, Shanghai Eye Hospital, Shanghai Vision Health Center & Shanghai Children Myopia Institute, Shanghai, China.
  • Zhang X; Department of Clinical Research, Shanghai Eye Disease Prevention and Treatment Center, Shanghai Eye Hospital, Shanghai Vision Health Center & Shanghai Children Myopia Institute, Shanghai, China.
  • Zou H; Department of Clinical Research, Shanghai Eye Disease Prevention and Treatment Center, Shanghai Eye Hospital, Shanghai Vision Health Center & Shanghai Children Myopia Institute, Shanghai, China.
  • Ang M; Centre for Eye Research Australia, Ophthalmology, University of Melbourne, Melbourne, VIC, Australia.
  • Tham CC; Institute of Translational Medicine, Shanghai Jiao Tong University, Shanghai, China.
  • Cheung CY; School of Computer Science, The University of Sydney, Sydney, NSW, Australia.
  • Pang CP; Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Kowloon, Hong Kong.
  • Sheng B; Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Kowloon, Hong Kong.
  • He X; Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Kowloon, Hong Kong.
  • Xu X; Department of Clinical Research, Shanghai Eye Disease Prevention and Treatment Center, Shanghai Eye Hospital, Shanghai Vision Health Center & Shanghai Children Myopia Institute, Shanghai, China.
NPJ Digit Med ; 7(1): 206, 2024 Aug 07.
Article in En | MEDLINE | ID: mdl-39112566
ABSTRACT
The increasing prevalence of myopia worldwide presents a significant public health challenge. A key strategy to combat myopia is with early detection and prediction in children as such examination allows for effective intervention using readily accessible imaging technique. To this end, we introduced DeepMyopia, an artificial intelligence (AI)-enabled decision support system to detect and predict myopia onset and facilitate targeted interventions for children at risk using routine retinal fundus images. Based on deep learning architecture, DeepMyopia had been trained and internally validated on a large cohort of retinal fundus images (n = 1,638,315) and then externally tested on datasets from seven sites in China (n = 22,060). Our results demonstrated robustness of DeepMyopia, with AUCs of 0.908, 0.813, and 0.810 for 1-, 2-, and 3-year myopia onset prediction with the internal test set, and AUCs of 0.796, 0.808, and 0.767 with the external test set. DeepMyopia also effectively stratified children into low- and high-risk groups (p < 0.001) in both test sets. In an emulated randomized controlled trial (eRCT) on the Shanghai outdoor cohort (n = 3303) where DeepMyopia showed effectiveness in myopia prevention compared to NonCyc-based model, with an adjusted relative reduction (ARR) of -17.8%, 95% CI -29.4%, -6.4%. DeepMyopia-assisted interventions attained quality-adjusted life years (QALYs) of 0.75 (95% CI 0.53, 1.04) per person and avoided blindness years of 13.54 (95% CI 9.57, 18.83) per 1 million persons compared to natural lifestyle with no active intervention. Our findings demonstrated DeepMyopia as a reliable and efficient AI-based decision support system for intervention guidance for children.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: NPJ Digit Med Year: 2024 Document type: Article Affiliation country: China Country of publication: United kingdom
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Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: NPJ Digit Med Year: 2024 Document type: Article Affiliation country: China Country of publication: United kingdom