{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T06:15:23Z","timestamp":1783577723103,"version":"3.55.0"},"reference-count":32,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T00:00:00Z","timestamp":1783555200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:p>\n                    The global surge in childhood myopia necessitates robust screening tools for early risk stratification; however, conventional predictive models often struggle with irregular follow-up intervals and fail to capture the continuous nature of refractive development. We propose Myo-ODE, a continuous-time framework based on Neural Ordinary Differential Equations (Neural ODEs) to predict high myopia risk. Unlike traditional discrete machine learning models, Myo-ODE parameterizes the derivative of the refractive state, allowing myopia progression to be represented as a continuous latent dynamic flow. This architecture explicitly accommodates non-uniform screening intervals and supports temporal interpolation and cautious short-term extrapolation within the observed follow-up horizon. Evaluated on a longitudinal dataset (\n                    <jats:italic>N<\/jats:italic>\n                    = 4,973), Myo-ODE achieved the highest F1-score of 0.8000 (95% CI: 0.7741\u20130.8256) and Recall of 0.7812 (95% CI: 0.7518\u20130.8103), while maintaining a competitive AUC of 0.9834 (95% CI: 0.9781\u20130.9887). Furthermore, our framework reconstructs individualized refractive progression trajectories and provides an interpretable estimate of the model-learned progression momentum of SE change. By bridging the gap between discrete clinical observations and continuous trajectory-level modeling, Myo-ODE offers a promising tool for personalized myopia surveillance in real-world screening environments.\n                  <\/jats:p>","DOI":"10.3389\/fpubh.2026.1897882","type":"journal-article","created":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T05:34:48Z","timestamp":1783575288000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Myo-ODE: continuous-time trajectory reconstruction and risk prediction of high myopia via neural ordinary differential equations"],"prefix":"10.3389","volume":"14","author":[{"given":"Na","family":"Zhao","sequence":"first","affiliation":[{"name":"School of Software, Yunnan University","place":["Kunming, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Runze","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Software, Yunnan University","place":["Kunming, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinhao","family":"Lu","sequence":"additional","affiliation":[{"name":"School of Software, Yunnan University","place":["Kunming, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhaoyu","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Software, Yunnan University","place":["Kunming, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cairui","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Ophthalmology, People's Hospital of Dali Bai Autonomous Prefecture","place":["Yunnan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chao","family":"Dai","sequence":"additional","affiliation":[{"name":"School of Software, Yunnan University","place":["Kunming, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiao","family":"Enbei","sequence":"additional","affiliation":[{"name":"College of International Students & Preparatory Education, Sichuan University","place":["Chengdu, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Information Engineering and Automation, Kunming University of Science and Technology","place":["Kunming, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,7,9]]},"reference":[{"key":"B1","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"},{"key":"B2","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"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.1167\/iovs.61.4.49","article-title":"The complications of myopia: a review and meta-analysis","author":"Haarman","year":"2020","journal-title":"Invest. 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