Dolgin E. Myopia boom. Nature. 2015;519:276–8.
Holden BA, Fricke TR, Wilson DA, Jong M, Naidoo KS, Sankaridurg P, et al. Global prevalence of myopia and high myopia and temporal trends from 2000 to 2050. Ophthalmology. 2016;123:1036–42.
Wong TY, Ferreira A, Hughes R, Carter G, Mitchell P. Epidemiology and disease burden of pathological myopia and myopic choroidal neovascularization: an evidence-based systematic review. J Ophthalmor. 2014;157:9–25.e12.
Morgan IG, Ohno Matsui K, Sou SM. Myopia. Lancet. 2012;379:1739–48.
Bullimore MA, Ritchie ER, Shah S, Levezir N, Bourne RRA, Flitcroft DI. Risks and benefits of myopia control. Ophthalmology. 2021;128:1561–79.
Pozarikiji A, Williams C, Hishi PG, Guggenheim JA. Quantile regression analysis reveals extensive evidence for gene-environment or gene-gene interactions in the development of myopia. commune biol. 2019;2:167.
Flitcroft DI. Complex interplay of retinal, optical, and environmental factors in the pathogenesis of myopia. Progretin Ocular Resistance 2012;31:622–60.
Wang X, He Q, Zhao X, Li H, Liu L, Wu D et al. Evaluation of neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in patients with high myopia. BMC Ophthalmall. 2022;22:464.
Isel E, Ucak T, Karakurt Y, Yilmaz H, Tasli NG, Turk A. Relationship between neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in severe axial myopia. Ocular immune inflammation. 2020;28:396–401.
Qi J, Pan W, Peng T, Zeng L, Li X, Chen Z et al. Elevated circulating levels of neutrophils and basophils are associated with myopic retinopathy. Int J Mol Sci. 2022;24:80.
Silegar AP, Amla AA. Correlation between neutrophil-to-lymphocyte ratio (NLR) and degree of myopia in medical students of University of Sumatra Utara. Eur Mod Stud J. 2021;5:436–41.
Google Scholar
Benke K, Benke G. Artificial intelligence and big data in public health. Int J Environ Res Public Health. 2018;15:2796.
Wen X, Leng P, Wang J, Yang G, Zu R, Jia X, et al. Clinlabomics: Utilizing clinical laboratory data through data mining strategies. BMC bioinformatics. 2022;23:387.
Obermeyer Z, Emmanuel EJ. Predicting the future – big data, machine learning, and clinical medicine. N Eng J Med 2016;375:1216–9.
Wu J, Zan X, Gao L, Zhao J, Fan J, Shi H et al. A machine learning method for identifying lung cancer based on routine blood indicators: a qualitative feasibility study. JMIR Medical Research Institute 2019;7:e13476.
Sørensen PD, Christensen H, Gray-Wausau-Laulsen S, Haldahl C, Brunslund I, Madsen JS. Using artificial intelligence in primary care settings to identify patients at risk for cancer. A risk prediction model based on routine clinical tests. Clin Chem Lab Medical. 2022;60:2005–16.
Li S, Li M, Wu J, Li Y, Han J, Cao W et al. Development and validation of a model based on routine blood parameters to screen for the occurrence of retinal detachment in high myopia associated with PPPM. EPMA J. 2023;14:219–33.
Choi KJ, Choi Jae, Roh HC, Eun JS, Kim JM, Shin YK A deep learning model for screening high myopia using multi-optical coherence tomography. Sci Rep. 2021;11:21663.
Foo LL, Lim GYS, Lanca C, Wong CW, Hoang QV, Zhang XJ et al. A deep learning system to predict 5-year risk of high myopia using pediatric fundus images. NPJ DigitMed. 2023;6:10.
Wang Y, Du R, Xie S, Chen C, Lu H, Xiong J, et al. A machine learning model for predicting long-term visual acuity in highly myopic eyes. JAMA Ophthalmology. 2023;141:1117–24.
Obkowski NA. Zhou XH. A prospective study on the accuracy of diagnostic tests when disease prevalence is low. Biostatistics. 2002;3:477–92.
Wan C, Li H, Cao GF, Jiang Q, Yang WH. An artificial intelligence risk classification method for severe myopia based on fundus images. J Clinical Medicine. 2021;10:4488.
Zuo H, Huang B, He J, Fang L, Huang M. Machine learning approaches in high myopia: a systematic review and meta-analysis. J Med Internet Res. 2025;27:e57644.
Council for Children with Disabilities, Pediatric Developmental Behavior Subcommittee, Bright Futures Steering Committee, and Home Health Initiative for Children with Special Needs Project Advisory Committee. Identifying infants and young children with developmental disabilities in health care settings: Algorithms for developmental monitoring and screening. Pediatrics. 2006;118:405–20.
Zhang R, Dong L, Yang Q, Zhou W, Wu H, Li Y et al. Screening for new risk factors associated with high myopia using machine learning. BMC Ophthalmall. 2022;22:405.
Vitek L, Žirasková A, Malikova I, Dostarova G, Jeremiašová L, Danzig V, et al. Serum bilirubin and markers of oxidative stress and inflammation in healthy populations and patients with different forms of atherosclerosis. Antioxidants (Basel). 2022;11:2118.
Patil K, Werner L, Carraro G, Gotlinger KH, Dunn MW, Schwartzman ML. Induction of heme oxygenase-1 reduces corneal inflammation and promotes wound healing after epithelial injury. Invest in Ospheremol Vis Sci. 2008;49:3379–86.
Yu, Q., Zhou, J.B. Scleral remodeling in the development of myopia. Int J Ophthalmol. 2022;15:510–4.
ying X, Ge J. The role of scleral changes in myopia progression: review and future directions. Klin Ophthalmol. 2025;19:1699–707.
Shao M, Wang S, Wan Y, Liu Z, Ma Y, Cao W et al. Association between serum total bilirubin levels and primary open-angle glaucoma patients in China: a cross-sectional case-control study. Oxid Med Cell Longev. 2023;2023:8206298.
Hui J, Tang K, Zhou Y, Cui X, Han Q. Causal effects of gut microbiota and metabolites on myopia and pathological myopia: A mediated Mendelian randomized study. Sci Rep. 2025;15:12928.
Duan X, Lu Q, Xue P, Zhang H, Dong Z, Yang F et al. Proteomic analysis of aqueous humor in myopic patients. Morbis. 2008;14:370–7.
Seko Y, Shimokawa H, Tokoro T. In vivo and in vitro association of retinoic acid and form deprivation myopia in chickens. Exp Eye Res. 1996;63:443–52.
Borrás T. A single gene links glaucoma stiffness to the vasculature. Exp Eye Res. 2017;158:13–22.
Kiefer AK, Tung JY, Du CB, Hines DA, Mountain JL, Franke U, et al. Genome-wide analysis points to a role for extracellular matrix remodeling, visual cycles, and neuronal development in myopia. PLoS Genet. 2013;9:e1003299.
Mao C, Zhang X, Liao M, Zhou F, Zhu X, Wang T, et al. Recalled age of myopia onset may predict the risk of high adult myopia in Chinese adults. Ophthalmic Research Institute 2024;67:266–74.
Velkicharla PK, Kanmari P, Das AV. The progression of myopia depends on age and severity of myopia. PLoS One. 2020;15:e0241759.
Du R, Xie S, Igarashi-Yokoi T, Watanabe S, Kazuto Uramoto, Hiroshi Takahashi, et al. Continuous increase in axial length and its risk factors in adults with high myopia. JAMA Ophthalmology. 2021;139:1096–103.
Gwinup G, Villarreal A. Relationship between serum glucose concentration and changes in refraction. Diabetes. 1976;25:29–31.
Li FF, Zhu MC, Shao YL, Lu F, Yi QY, Huang XF. Causal relationship between glycemic characteristics and myopia. Invest in Ospheremol Vis Sci. 2023;64:7.
Francisco BM, Salvador M, Amparo N. Oxidative stress in myopia. Oxid Med Cell Longev. 2015;2015:750637.
Lin X, Lei Y, Pan M, Hu C, Xie B, Wu W et al. Enhanced scleral glycolysis promotes myopia through histone lactylation. Cell Metab. 2024;36:511–25.e7.
Berticat C, Venturini E, Daien V, Goldberg M, Zins M, Raymond M. Association between myopia and refined carbohydrate intake: a cross-sectional study from the Constances cohort. Clin Nutr Espen. 2025;67:329–37.
Wyss M, Kaddurah-Daouk R. Creatine and creatinine metabolism. Physiol Rev. 2000;80:1107–213.
Ruamviboonsuk V, Lanca C, Grzybowski A. Biomarkers: a promising tool for the diagnosis, prognosis, and treatment of myopia. J Clinical Medicine. 2024;13:6754.
Wen K, Shao X, Li Y, Li Y, Li Y, Wang Q et al Plasminogen protein is associated with high myopia as revealed by iTRAQ-based proteomic analysis of aqueous humor. Sci Rep. 2021;11:8789.
Tang YP, Zhang XB, Hu ZX, Lin K, Lin Z, Chen TY et al. Vitreous metabolomic signatures of pathological myopia with complications. Eyes (Rondo). 2023;37:2987–93.
Zhang Z, Lv L, Chen D, Li F, Zhou J. Molecular changes in intraocular fluid: implications for myopia. Int J Biol Sci. 2024;20:5330–42.
Wiens J, Saria S, Sendak M, Ghassemi M, Liu VX, Doshi-Velez F, et al. Do no harm: A roadmap for responsible machine learning for healthcare. Nat Med. 2019;25:1337–40.
