{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T16:10:53Z","timestamp":1792858253210,"version":"4.5.0"},"reference-count":37,"publisher":"American Medical Association (AMA)","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAMA Netw Open"],"abstract":"\n Importance<\/jats:title>\n Childhood myopia is a global health concern with escalating prevalence and can lead to severe irreversible visual impairment. Early prediction of myopia progression is crucial for timely intervention to prevent high myopia and associated complications.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n To develop and validate a quantitative method, based on a deep learning method and using only fundus images and baseline refraction data, to predict both myopia progression trajectory and high myopia risk in schoolchildren.<\/jats:p>\n <\/jats:sec>\n \n Design, Setting, and Participants<\/jats:title>\n This longitudinal school-based cohort study (Anyang Childhood Eye Study) was conducted from February 2012 to May 2018, with annual follow-up examinations from February 2013 to May 2018. Grade 1 students, aged 6 to 9 years, were recruited from 11 randomly selected urban primary schools in Anyang, Henan Province, China. Children who received myopia control treatments, had amblyopia, or underwent strabismus surgery were excluded. Two independent external validation cohorts were used: the Lhasa cohort (predominantly consisting of Tibetan children) and the Beijing cohort (predominantly consisting of Han Chinese children). Data analysis was performed from July 2024 to July 2025.<\/jats:p>\n <\/jats:sec>\n \n Main Outcomes and Measures<\/jats:title>\n Performance of a novel deep learning model, created from combining convolutional neural network (34-layer residual network) and recurrent neural network (long short-term memory network). Area under the curve (AUC) was used to assess myopia and high myopia risk prediction, and mean absolute error (MAE) was used to assess spherical equivalent refraction (SER) prediction. Myopia was defined as SER of \u20130.5 D or less, and high myopia was defined as \u20136.0 D or less, using cycloplegic autorefraction.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n Among the 3048 children (mean [SD] age, 7.1\u2009[0.4] years; 1716 females [56.3%]) included, the baseline prevalence rate of myopia was 5.71% (174) and high myopia was 0.5% (15). The deep learning model achieved AUC scores of 0.941 (95% CI, 0.936-0.946) for myopia risk prediction and 0.985 (95% CI, 0.982-0.988) for high myopia risk prediction, with an overall MAE of 0.322 D per year for SER prediction. External validation in the Beijing cohort (n\u2009=\u2009130; mean [SD] age, 9.9 [3.7] years; 82 males [63.1%]; 128 Han Chinese [98.5%], 2 Man Chu [1.5%]) and the Lhasa cohort (n\u2009=\u20091039; mean [SD] age, 6.8 [0.5] years; 536 males [51.6%]; 29 Han Chinese [2.8%], 1007 Tibetan [96.9%], 3 [0.2%] from other ethnic minority groups) demonstrated maintained cross-ethnicity performance by the model, with an MAE of 0.355 D and 0.261 D per year, respectively.<\/jats:p>\n <\/jats:sec>\n \n Conclusions and Relevance<\/jats:title>\n In this cohort study, a deep learning model, using minimal baseline data, provided highly accurate prediction of myopia and high myopia risk. This deep learning approach suggests the utility of large-scale screening and early-intervention efforts in resource-limited settings.<\/jats:p>\n <\/jats:sec>","DOI":"10.1001\/jamanetworkopen.2025.53543","type":"journal-article","created":{"date-parts":[[2026,1,26]],"date-time":"2026-01-26T16:00:31Z","timestamp":1769443231000},"page":"e2553543","source":"Crossref","is-referenced-by-count":14,"title":["Deep Learning Prediction of Childhood Myopia Progression Using Fundus Image and Refraction Data"],"prefix":"10.1001","volume":"9","author":[{"given":"Meng-Tian","family":"Kang","sequence":"first","affiliation":[{"name":"Beijing Tongren Eye Center, Beijing Tongren Hospital, Beijing Institute of Ophthalmology, Beijing Key Laboratory of Intelligent Diagnosis Technology and Equipment for Optic Nerve-Related Eye Diseases, National Engineering Research Center for Ophthalmology, Engineering Research Center of Ophthalmic Equipment and Materials (Ministry of Education), Capital Medical University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yansong","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ningli","family":"Wang","sequence":"additional","affiliation":[{"name":"Beijing Tongren Eye Center, Beijing Tongren Hospital, Beijing Institute of Ophthalmology, Beijing Key Laboratory of Intelligent Diagnosis Technology and Equipment for Optic Nerve-Related Eye Diseases, National Engineering Research Center for Ophthalmology, Engineering Research Center of Ophthalmic Equipment and Materials (Ministry of Education), Capital Medical University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing","family":"Fu","sequence":"additional","affiliation":[{"name":"Beijing Tongren Eye Center, Beijing Tongren Hospital, Beijing Institute of Ophthalmology, Beijing Key Laboratory of Intelligent Diagnosis Technology and Equipment for Optic Nerve-Related Eye Diseases, National Engineering Research Center for Ophthalmology, Engineering Research Center of Ophthalmic Equipment and Materials (Ministry of Education), Capital Medical University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ankang","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuanyuan","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Beihang University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongbei","family":"Meng","sequence":"additional","affiliation":[{"name":"School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuemeng","family":"Li","sequence":"additional","affiliation":[{"name":"School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shengbo","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuhang","family":"Chen","sequence":"additional","affiliation":[{"name":"Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hubin","family":"Zhao","sequence":"additional","affiliation":[{"name":"Division of Surgery and Interventional Science, University College London, Stanmore, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guohua","family":"Hu","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, The Chinese University of Hong Kong, Shatin, N. T., Hong Kong SAR, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Wang","sequence":"additional","affiliation":[{"name":"AI Medical Image Division, Thorough Future Inc, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanning","family":"Dai","sequence":"additional","affiliation":[{"name":"Centers of Excellence, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arokia","family":"Nathan","sequence":"additional","affiliation":[{"name":"Department of Engineering, University of Cambridge, Cambridge, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peter","family":"Smielewski","sequence":"additional","affiliation":[{"name":"Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuo","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shi-Ming","family":"Li","sequence":"additional","affiliation":[{"name":"Beijing Tongren Eye Center, Beijing Tongren Hospital, Beijing Institute of Ophthalmology, Beijing Key Laboratory of Intelligent Diagnosis Technology and Equipment for Optic Nerve-Related Eye Diseases, National Engineering Research Center for Ophthalmology, Engineering Research Center of Ophthalmic Equipment and Materials (Ministry of Education), Capital Medical University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"10","published-online":{"date-parts":[[2026,1,26]]},"reference":[{"issue":"5","key":"zoi251427r1","doi-asserted-by":"publisher","first-page":"1036","DOI":"10.1016\/j.ophtha.2016.01.006","article-title":"Global prevalence of myopia and high myopia and temporal trends from 2000 through 2050.","volume":"123","author":"Holden","year":"2016","journal-title":"Ophthalmology"},{"issue":"9827","key":"zoi251427r2","doi-asserted-by":"publisher","first-page":"1739","DOI":"10.1016\/S0140-6736(12)60272-4","article-title":"Myopia.","volume":"379","author":"Morgan","year":"2012","journal-title":"Lancet"},{"issue":"6","key":"zoi251427r3","doi-asserted-by":"publisher","first-page":"1248","DOI":"10.1111\/opo.13366","article-title":"High myopia: reviews of myopia control strategies and myopia complications.","volume":"44","author":"Shah","year":"2024","journal-title":"Ophthalmic Physiol Opt"},{"issue":"4","key":"zoi251427r4","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1167\/iovs.62.4.17","article-title":"Rapid myopic progression in childhood is associated with teenage high myopia.","volume":"62","author":"Lanca","year":"2021","journal-title":"Invest Ophthalmol Vis Sci"},{"issue":"11","key":"zoi251427r5","doi-asserted-by":"publisher","first-page":"1482","DOI":"10.1136\/bjophthalmol-2019-315575","article-title":"Review: myopia control strategies recommendations from the 2018 WHO\/IAPB\/BHVI Meeting on Myopia.","volume":"104","author":"Ang","year":"2020","journal-title":"Br J Ophthalmol"},{"issue":"8","key":"zoi251427r6","doi-asserted-by":"publisher","first-page":"2800","DOI":"10.4103\/ijo.IJO_2098_21","article-title":"Current concepts in the management of childhood myopia.","volume":"70","author":"Dhiman","year":"2022","journal-title":"Indian J Ophthalmol"},{"issue":"90","key":"zoi251427r7","first-page":"35","article-title":"Myopia: a growing global problem with sight-threatening complications.","volume":"28","author":"Holden","year":"2015","journal-title":"Community Eye Health"},{"issue":"2","key":"zoi251427r8","doi-asserted-by":"publisher","first-page":"463","DOI":"10.3390\/ijerph17020463","article-title":"Prediction of myopia in adolescents through machine learning methods.","volume":"17","author":"Yang","year":"2020","journal-title":"Int J Environ Res Public Health"},{"issue":"5","key":"zoi251427r9","doi-asserted-by":"publisher","first-page":"921","DOI":"10.1038\/s41433-021-01805-6","article-title":"Myopia prediction: a systematic review.","volume":"36","author":"Han","year":"2022","journal-title":"Eye (Lond)"},{"issue":"11","key":"zoi251427r10","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pmed.1002674","article-title":"Prediction of myopia development among Chinese school-aged children using refraction data from electronic medical records: a retrospective, multicentre machine learning study.","volume":"15","author":"Lin","year":"2018","journal-title":"PLoS Med"},{"issue":"1","key":"zoi251427r11","doi-asserted-by":"publisher","DOI":"10.1080\/07853890.2024.2331056","article-title":"Development of a nomogram for predicting myopia risk among school-age children: a case-control study.","volume":"56","author":"Mu","year":"2024","journal-title":"Ann Med"},{"key":"zoi251427r12","doi-asserted-by":"publisher","first-page":"96","DOI":"10.1016\/j.ajo.2022.05.027","article-title":"Development and validation of a novel nomogram for predicting the occurrence of myopia in schoolchildren: a prospective cohort study.","volume":"242","author":"Guo","year":"2022","journal-title":"Am J Ophthalmol"},{"issue":"1","key":"zoi251427r13","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1038\/s41746-023-00752-8","article-title":"Deep learning system to predict the 5-year risk of high myopia using fundus imaging in children.","volume":"6","author":"Foo","year":"2023","journal-title":"NPJ Digit Med"},{"issue":"19","key":"zoi251427r14","doi-asserted-by":"publisher","first-page":"4488","DOI":"10.3390\/jcm10194488","article-title":"An artificial intelligent risk classification method of high myopia based on fundus images.","volume":"10","author":"Wan","year":"2021","journal-title":"J Clin Med"},{"issue":"1","key":"zoi251427r15","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1186\/s40662-022-00285-3","article-title":"Automated detection of myopic maculopathy from color fundus photographs using deep convolutional neural networks.","volume":"9","author":"Li","year":"2022","journal-title":"Eye Vis (Lond)"},{"issue":"2","key":"zoi251427r16","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1038\/s41433-023-02680-z","article-title":"Performance of artificial intelligence for the detection of pathological myopia from colour fundus images: a systematic review and meta-analysis.","volume":"38","author":"Prashar","year":"2024","journal-title":"Eye (Lond)"},{"issue":"12","key":"zoi251427r17","doi-asserted-by":"publisher","first-page":"1235","DOI":"10.1016\/j.oret.2021.02.006","article-title":"Deep learning approach for automated detection of myopic maculopathy and pathologic myopia in fundus images.","volume":"5","author":"Du","year":"2021","journal-title":"Ophthalmol Retina"},{"issue":"1","key":"zoi251427r18","doi-asserted-by":"publisher","first-page":"469","DOI":"10.1007\/s40123-022-00621-9","article-title":"Efficacy of a deep learning system for screening myopic maculopathy based on color fundus photographs.","volume":"12","author":"Wang","year":"2023","journal-title":"Ophthalmol Ther"},{"key":"zoi251427r19","doi-asserted-by":"publisher","first-page":"305","DOI":"10.1016\/j.neunet.2022.10.023","article-title":"Improved residual network based on norm-preservation for visual recognition.","volume":"157","author":"Mahaur","year":"2023","journal-title":"Neural Netw"},{"key":"zoi251427r20","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2021.103737","article-title":"Incorporating multi-level CNN and attention mechanism for Chinese clinical named entity recognition.","volume":"116","author":"Kong","year":"2021","journal-title":"J Biomed Inform"},{"issue":"20","key":"zoi251427r21","doi-asserted-by":"publisher","first-page":"2191","DOI":"10.1001\/jama.2013.281053","article-title":"World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects.","volume":"310","author":"World Medical Association","year":"2013","journal-title":"JAMA"},{"issue":"6","key":"zoi251427r22","doi-asserted-by":"publisher","first-page":"348","DOI":"10.3109\/09286586.2013.842596","article-title":"Design, methodology and baseline data of a school-based cohort study in Central China: the Anyang Childhood Eye Study.","volume":"20","author":"Li","year":"2013","journal-title":"Ophthalmic Epidemiol"},{"issue":"1","key":"zoi251427r23","doi-asserted-by":"publisher","first-page":"289","DOI":"10.1186\/s12967-024-05075-0","article-title":"Development and validation of predictive models for myopia onset and progression using extensive 15-year refractive data in children and adolescents.","volume":"22","author":"Zhao","year":"2024","journal-title":"J Transl Med"},{"issue":"6","key":"zoi251427r24","doi-asserted-by":"publisher","first-page":"683","DOI":"10.1001\/jamaophthalmol.2015.0471","article-title":"Prediction of juvenile-onset myopia.","volume":"133","author":"Zadnik","year":"2015","journal-title":"JAMA Ophthalmol"},{"issue":"3","key":"zoi251427r25","doi-asserted-by":"publisher","first-page":"383","DOI":"10.1016\/j.ophtha.2020.07.045","article-title":"Detection of progressive glaucomatous optic nerve damage on fundus photographs with deep learning.","volume":"128","author":"Medeiros","year":"2021","journal-title":"Ophthalmology"},{"issue":"22","key":"zoi251427r26","doi-asserted-by":"publisher","first-page":"2211","DOI":"10.1001\/jama.2017.18152","article-title":"Development and validation of a deep learning system for diabetic retinopathy and related eye diseases using retinal images from multiethnic populations with diabetes.","volume":"318","author":"Ting","year":"2017","journal-title":"JAMA"},{"issue":"5","key":"zoi251427r27","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1167\/iovs.62.5.5","article-title":"IMI pathologic myopia.","volume":"62","author":"Ohno-Matsui","year":"2021","journal-title":"Invest Ophthalmol Vis Sci"},{"key":"zoi251427r28","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/bs.pbr.2020.06.014","article-title":"Glaucoma neurodegeneration and myopia.","volume":"257","author":"Jonas","year":"2020","journal-title":"Prog Brain Res"},{"key":"zoi251427r29","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1016\/j.preteyeres.2018.12.001","article-title":"Posterior staphyloma in pathologic myopia.","volume":"70","author":"Ohno-Matsui","year":"2019","journal-title":"Prog Retin Eye Res"},{"issue":"5","key":"zoi251427r30","doi-asserted-by":"publisher","first-page":"424","DOI":"10.1097\/OPX.0000000000001883","article-title":"The limited value of prior change in predicting future progression of juvenile-onset myopia.","volume":"99","author":"Mutti","year":"2022","journal-title":"Optom Vis Sci"},{"issue":"1","key":"zoi251427r31","doi-asserted-by":"publisher","first-page":"279","DOI":"10.1186\/s12886-021-02036-9","article-title":"Predicting the onset of myopia in children: results from the CLEERE study.","volume":"21","author":"Mutti","year":"2021","journal-title":"BMC Ophthalmol"},{"issue":"1","key":"zoi251427r32","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1186\/s12886-016-0382-2","article-title":"The differences in level of trait anxiety among girls and boys aged 13-17 years with myopia and emmetropia.","volume":"16","author":"Lazarczyk","year":"2016","journal-title":"BMC Ophthalmol"},{"issue":"5","key":"zoi251427r33","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1167\/iovs.62.5.2","article-title":"IMI impact of myopia.","volume":"62","author":"Sankaridurg","year":"2021","journal-title":"Invest Ophthalmol Vis Sci"},{"issue":"3","key":"zoi251427r34","doi-asserted-by":"publisher","first-page":"338","DOI":"10.1016\/j.ophtha.2018.10.029","article-title":"Potential lost productivity resulting from the global burden of myopia: systematic review, meta-analysis, and modeling.","volume":"126","author":"Naidoo","year":"2019","journal-title":"Ophthalmology"},{"issue":"4","key":"zoi251427r35","doi-asserted-by":"publisher","first-page":"408","DOI":"10.1001\/jamaophthalmol.2018.6906","article-title":"Predictors of spectacle wear and reasons for nonwear in students randomized to ready-made or custom-made spectacles: results of secondary objectives from a randomized noninferiority trial.","volume":"137","author":"Morjaria","year":"2019","journal-title":"JAMA Ophthalmol"},{"issue":"1","key":"zoi251427r36","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1097\/APO.0000000000000487","article-title":"How to conduct school myopia screening: comparison among myopia screening tests and determination of associated cutoffs.","volume":"11","author":"Wang","year":"2022","journal-title":"Asia Pac J Ophthalmol (Phila)"},{"issue":"12","key":"zoi251427r37","doi-asserted-by":"publisher","first-page":"1479","DOI":"10.1097\/OPX.0000000000000095","article-title":"Myopia screening: combining visual acuity and noncycloplegic autorefraction.","volume":"90","author":"Ma","year":"2013","journal-title":"Optom Vis Sci"}],"container-title":["JAMA Network Open"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/jamanetwork.com\/journals\/jamanetworkopen\/articlepdf\/2844223\/kang_2026_oi_251427_1768515251.43724.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,26]],"date-time":"2026-01-26T16:00:31Z","timestamp":1769443231000},"score":1,"resource":{"primary":{"URL":"https:\/\/jamanetwork.com\/journals\/jamanetworkopen\/fullarticle\/2844223"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,26]]},"references-count":37,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,1,2]]}},"URL":"https:\/\/doi.org\/10.1001\/jamanetworkopen.2025.53543","relation":{},"ISSN":["2574-3805"],"issn-type":[{"value":"2574-3805","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,26]]}}}