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. 2024 Aug 7;7:206. doi: 10.1038/s41746-024-01204-7

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© The Author(s) 2024

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

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Fig. 1 — a Dataset used in this study. b Evaluation and application of DeepMyopia. DeepMyopia enables myopia detection, myopia onset prediction within a 3-year timeframe, as well as risk stratification of myopia onset. An emulating randomized controlled trial (eRCT) was performed based on the risk stratification, extending the applicability of DeepMyopia in public health. c Application scenarios for DeepMyopia. DeepMyopia could identify myopic children among children population and predict the risk for the future myopia onset in non-myopic children, such that provided guided intervention. d The architecture of the proposed DeepMyopia. AL axial length.