{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T05:52:47Z","timestamp":1775713967167,"version":"3.50.1"},"reference-count":66,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T00:00:00Z","timestamp":1775692800000},"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. Cell Dev. Biol."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Refractive error and dry eye are highly prevalent ocular conditions that significantly impair the quality of life and impose a substantial burden on individuals and society. Growing evidence suggests a correlation between these two conditions. This study aimed to develop and validate a machine learning (ML) model to accurately predict the risk of concurrent dry eye comorbidities in patients with refractive error.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Data from Xiamen Eye Center outpatient database (1st January 2024 to 28th February 2025) were analyzed (n = 114,579). Hyperparameter optimization,\n                      <jats:italic>Spearman<\/jats:italic>\n                      correlation analysis, and logistic regression analyses were performed. The final feature set was determined using a Random Forest algorithm with the sequential forward selection technique. Eight ML algorithms were evaluated through ten-fold cross-validation. The optimal model was selected based on a comprehensive assessment of the receiver operating characteristic curve, precision-recall curve, and decision curve analysis. For the best-performing model, SHapley Additive exPlanations and partial dependence plots were utilized to interpret the importance and interactions of risk factors.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Baseline characteristics were comparable between the training set and the internal test set, while significant differences were observed in multiple baseline characteristics between dry eye group and non-dry eye group among subjects with refractive error. Based on ten selected feature variables, the tabular prior-data fitted network (TabPFN) model demonstrated the best performance, showing high screening efficacy with both specificity and accuracy reaching 0.945. The interaction analysis revealed that a longer duration of refractive error was associated with a higher risk of dry eye, a relationship that was particularly pronounced among older and female patients. Furthermore, an online web calculator was developed to deploy this diagnostic prediction model.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>This study developed a high-performance and interpretable ML system based on a large-scale real-world clinical dataset for the early prediction of concurrent dry eye risk in patients with refractive error. The system holds significant potential as a predictive aid for clinical decision-making, enabling more timely and personalized patient management, thereby offering substantial clinical value and promising application prospects.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fcell.2026.1770427","type":"journal-article","created":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T05:20:37Z","timestamp":1775712037000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["A TabPFN-based prediction system for refractive error and dry eye comorbidity: a retrospective study using large-scale real-world data"],"prefix":"10.3389","volume":"14","author":[{"given":"Danyi","family":"Qin","sequence":"first","affiliation":[{"name":"Xiamen University affiliated Xiamen Eye Center, Fujian Provincial Key Laboratory of Ophthalmology and Visual Science, Fujian Engineering and Research Center of Eye Regenerative Medicine, School of Medicine, Eye Institute of Xiamen University, Xiamen University","place":["Xiamen, Fujian, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenying","family":"Guan","sequence":"additional","affiliation":[{"name":"Xiamen University affiliated Xiamen Eye Center, Fujian Provincial Key Laboratory of Ophthalmology and Visual Science, Fujian Engineering and Research Center of Eye Regenerative Medicine, School of Medicine, Eye Institute of Xiamen University, Xiamen University","place":["Xiamen, Fujian, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shinan","family":"Wu","sequence":"additional","affiliation":[{"name":"Xiamen University affiliated Xiamen Eye Center, Fujian Provincial Key Laboratory of Ophthalmology and Visual Science, Fujian Engineering and Research Center of Eye Regenerative Medicine, School of Medicine, Eye Institute of Xiamen University, Xiamen University","place":["Xiamen, Fujian, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Changsheng","family":"Xu","sequence":"additional","affiliation":[{"name":"Xiamen University affiliated Xiamen Eye Center, Fujian Provincial Key Laboratory of Ophthalmology and Visual Science, Fujian Engineering and Research Center of Eye Regenerative Medicine, School of Medicine, Eye Institute of Xiamen University, Xiamen University","place":["Xiamen, Fujian, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuwen","family":"Liu","sequence":"additional","affiliation":[{"name":"Xiamen University affiliated Xiamen Eye Center, Fujian Provincial Key Laboratory of Ophthalmology and Visual Science, Fujian Engineering and Research Center of Eye Regenerative Medicine, School of Medicine, Eye Institute of Xiamen University, Xiamen University","place":["Xiamen, Fujian, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bing","family":"Yan","sequence":"additional","affiliation":[{"name":"Xiamen University affiliated Xiamen Eye Center, Fujian Provincial Key Laboratory of Ophthalmology and Visual Science, Fujian Engineering and Research Center of Eye Regenerative Medicine, School of Medicine, Eye Institute of Xiamen University, Xiamen University","place":["Xiamen, Fujian, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingyao","family":"Lv","sequence":"additional","affiliation":[{"name":"Xiamen University affiliated Xiamen Eye Center, Fujian Provincial Key Laboratory of Ophthalmology and Visual Science, Fujian Engineering and Research Center of Eye Regenerative Medicine, School of Medicine, Eye Institute of Xiamen University, Xiamen University","place":["Xiamen, Fujian, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoxin","family":"Li","sequence":"additional","affiliation":[{"name":"Xiamen University affiliated Xiamen Eye Center, Fujian Provincial Key Laboratory of Ophthalmology and Visual Science, Fujian Engineering and Research Center of Eye Regenerative Medicine, School of Medicine, Eye Institute of Xiamen University, Xiamen University","place":["Xiamen, Fujian, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zuguo","family":"Liu","sequence":"additional","affiliation":[{"name":"Xiamen University affiliated Xiamen Eye Center, Fujian Provincial Key Laboratory of Ophthalmology and Visual Science, Fujian Engineering and Research Center of Eye Regenerative Medicine, School of Medicine, Eye Institute of Xiamen University, Xiamen University","place":["Xiamen, Fujian, China"]},{"name":"Department of Ophthalmology, Hengyang Medical School, The First Affiliated Hospital of University of South China, University of South China","place":["Hengyang, Hunan, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2026,4,9]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"3643","DOI":"10.3390\/jcm11133643","article-title":"Prevalence of comorbidity between dry eye and allergic conjunctivitis: a systematic review and meta-analysis","volume":"11","author":"Akasaki","year":"2022","journal-title":"J. Clin. Med."},{"key":"B2","doi-asserted-by":"publisher","first-page":"138","DOI":"10.3390\/jimaging9070138","article-title":"VGG16 feature extractor with extreme gradient boost classifier for pancreas cancer prediction","volume":"9","author":"Bakasa","year":"2023","journal-title":"J. Imaging"},{"key":"B3","doi-asserted-by":"publisher","first-page":"e144","DOI":"10.1016\/S2214-109X(20)30489-7","article-title":"Causes of blindness and vision impairment in 2020 and trends over 30 years, and prevalence of avoidable blindness in relation to VISION 2020: the right to sight: an analysis for the global burden of disease study","volume":"9","author":"Blindness","year":"2021","journal-title":"Lancet Glob. Health"},{"key":"B4","doi-asserted-by":"publisher","first-page":"438","DOI":"10.1016\/j.jtos.2017.05.011","article-title":"TFOS DEWS II pathophysiology report","volume":"15","author":"Bron","year":"2017","journal-title":"Ocul. Surf."},{"key":"B5","doi-asserted-by":"publisher","first-page":"101073","DOI":"10.1016\/j.patter.2024.101073","article-title":"FLEX-SMOTE: synthetic over-sampling technique that flexibly adjusts to different minority class distributions","volume":"5","author":"Bunkhumpornpat","year":"2024","journal-title":"Patterns (N Y)"},{"key":"B6","doi-asserted-by":"publisher","first-page":"17473","DOI":"10.1038\/s41598-025-01309-3","article-title":"Correlation between binocular vision function and visual fatigue in school-age children with myopic anisometropia","volume":"15","author":"Cao","year":"2025","journal-title":"Sci. Rep."},{"key":"B7","doi-asserted-by":"publisher","first-page":"1731","DOI":"10.1016\/j.ophtha.2016.04.005","article-title":"Automated identification of lesion activity in neovascular age-related macular degeneration","volume":"123","author":"Chakravarthy","year":"2016","journal-title":"Ophthalmology"},{"key":"B8","doi-asserted-by":"publisher","first-page":"e0312725","DOI":"10.1371\/journal.pone.0312725","article-title":"Prevalence of symptomatic dry eye and influencing factors among Chinese adolescents: a cross-sectional study","volume":"19","author":"Chen","year":"2024","journal-title":"PLoS One"},{"key":"B9","doi-asserted-by":"publisher","first-page":"564","DOI":"10.3760\/cma.j.cn112142-20210429-00196","article-title":"Ocular surface and tear film diseases group of ophthalmology committee of cross-straits medicine exchange A, ocular S, dry eye group of Chinese ophthalmologist A. Expert consensus on dry eye in China: dry eye related to eye surgery","volume":"57","year":"2021","journal-title":"Zhonghua Yan Ke Za Zhi."},{"key":"B10","doi-asserted-by":"publisher","first-page":"968","DOI":"10.3760\/cma.j.cn112142-20240517-00227","article-title":"Chinese expert consensus on the diagnosis and treatment of dry eye","volume":"60","year":"2024","journal-title":"Zhonghua Yan Ke Za Zhi."},{"key":"B11","doi-asserted-by":"publisher","first-page":"690","DOI":"10.1080\/08820538.2023.2204931","article-title":"Real life impact of dry eye disease","volume":"38","author":"Cutrupi","year":"2023","journal-title":"Semin. Ophthalmol."},{"key":"B12","doi-asserted-by":"publisher","first-page":"584","DOI":"10.1038\/s41591-023-02702-z","article-title":"A deep learning system for predicting time to progression of diabetic retinopathy","volume":"30","author":"Dai","year":"2024","journal-title":"Nat. Med."},{"key":"B13","doi-asserted-by":"publisher","first-page":"252","DOI":"10.1016\/j.ajo.2021.01.018","article-title":"Multidisease deep learning neural network for the diagnosis of corneal diseases","volume":"226","author":"Elsawy","year":"2021","journal-title":"Am. J. Ophthalmol."},{"key":"B14","doi-asserted-by":"publisher","first-page":"653","DOI":"10.4103\/ijo.IJO_1103_17","article-title":"Correlation between dry eye and refractive error in Saudi young adults using noninvasive keratograph 4","volume":"66","author":"Fahmy","year":"2018","journal-title":"Indian J. Ophthalmol."},{"key":"B15","doi-asserted-by":"publisher","first-page":"583","DOI":"10.3390\/ma16020583","article-title":"Ensemble machine-learning-based prediction models for the compressive strength of recycled powder mortar","volume":"16","author":"Fei","year":"2023","journal-title":"Mater. (Basel)"},{"key":"B16","doi-asserted-by":"publisher","first-page":"506","DOI":"10.1186\/s12888-025-06913-1","article-title":"Development and validation of a risk prediction model for depression in patients with chronic obstructive pulmonary disease","volume":"25","author":"Feng","year":"2025","journal-title":"BMC Psychiatry"},{"key":"B17","doi-asserted-by":"publisher","first-page":"652","DOI":"10.1002\/bimj.201800148","article-title":"Tuning model parameters in class-imbalanced learning with precision-recall curve","volume":"61","author":"Fu","year":"2019","journal-title":"Biom J."},{"key":"B18","doi-asserted-by":"publisher","first-page":"2588285","DOI":"10.1080\/07853890.2025.2588285","article-title":"A machine-learning model to identify concurrent vascular disease in symptomatic patients with chronic obstructive pulmonary disease","volume":"57","author":"Gu","year":"2025","journal-title":"Ann. Med."},{"key":"B19","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1167\/iovs.61.4.49","article-title":"The complications of myopia: a review and meta-analysis","volume":"61","author":"Haarman","year":"2020","journal-title":"Invest Ophthalmol. Vis. Sci."},{"key":"B20","doi-asserted-by":"publisher","first-page":"e29715","DOI":"10.1016\/j.heliyon.2024.e29715","article-title":"Crosstalk between heredity and environment in myopia: an overview","volume":"10","author":"Hao","year":"2024","journal-title":"Heliyon"},{"key":"B21","doi-asserted-by":"publisher","first-page":"10891","DOI":"10.1038\/s41598-022-15023-x","article-title":"Relation between dry eye and myopia based on tear film breakup time, higher order aberration, choroidal thickness, and axial length","volume":"12","author":"Hazra","year":"2022","journal-title":"Sci. Rep."},{"key":"B22","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":"B23","doi-asserted-by":"publisher","first-page":"319","DOI":"10.1038\/s41586-024-08328-6","article-title":"Accurate predictions on small data with a tabular foundation model","volume":"637","author":"Hollmann","year":"2025","journal-title":"Nature"},{"key":"B24","doi-asserted-by":"publisher","first-page":"1991","DOI":"10.2147\/OPTH.S444765","article-title":"A possible reciprocal relationship between myopia and dry eye disease in Japanese teenagers","volume":"18","author":"Ibrahim","year":"2024","journal-title":"Clin. Ophthalmol."},{"key":"B25","doi-asserted-by":"publisher","first-page":"575","DOI":"10.1016\/j.jtos.2017.05.006","article-title":"TFOS DEWS II management and therapy report","volume":"15","author":"Jones","year":"2017","journal-title":"Ocul. Surf."},{"key":"B26","doi-asserted-by":"publisher","first-page":"842607","DOI":"10.3389\/fimmu.2022.842607","article-title":"Gradient boosting machine learning model for defective endometrial receptivity prediction by macrophage-endometrium interaction modules","volume":"13","author":"Li","year":"2022","journal-title":"Front. Immunol."},{"key":"B27","doi-asserted-by":"publisher","first-page":"362","DOI":"10.1136\/bjo-2024-325427","article-title":"Global prevalence, trend and projection of myopia in children and adolescents from 1990 to 2050: a comprehensive systematic review and meta-analysis","volume":"109","author":"Liang","year":"2025","journal-title":"Br. J. Ophthalmol."},{"key":"B28","doi-asserted-by":"publisher","first-page":"1207","DOI":"10.1136\/bjo-2024-326726","article-title":"Current status of school vision screening-rationale, models, impact and challenges: a review","volume":"109","author":"Little","year":"2025","journal-title":"Br. J. Ophthalmol."},{"key":"B29","volume-title":"New machine learning algorithm: Random forest. International conference on information computing and applications","author":"Liu","year":"2012"},{"key":"B30","doi-asserted-by":"publisher","first-page":"e22458","DOI":"10.1016\/j.heliyon.2023.e22458","article-title":"Prediction model for hepatocellular carcinoma recurrence after hepatectomy: machine learning-based development and interpretation study","volume":"9","author":"Liu","year":"2023","journal-title":"Heliyon"},{"key":"B31","doi-asserted-by":"publisher","first-page":"1611216","DOI":"10.3389\/fcell.2025.1611216","article-title":"Deep learning-driven approach for cataract management: towards precise identification and predictive analytics","volume":"13","author":"Lu","year":"2025","journal-title":"Front. Cell. Dev. Biol."},{"key":"B32","doi-asserted-by":"publisher","first-page":"1443","DOI":"10.1016\/j.jtcvs.2021.08.009","article-title":"Commentary: to classify means to choose a threshold","volume":"165","author":"Lyu","year":"2023","journal-title":"J. Thorac. Cardiovasc Surg."},{"key":"B33","article-title":"Feature selection using sequential forward selection and classification applying artificial metaplasticity neural network","volume-title":"Iecon 2010 - 36th annual conference on","author":"Marcano-Cedeo","year":"2010"},{"key":"B34","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1097\/APO.0000000000000492","article-title":"The impact of hyperopia on academic performance among children: a systematic review","volume":"11","author":"Mavi","year":"2022","journal-title":"Asia Pac J. Ophthalmol. (Phila)."},{"key":"B35","doi-asserted-by":"publisher","first-page":"224","DOI":"10.3390\/cells11020224","article-title":"Sex hormones, growth hormone, and the cornea","volume":"11","author":"McKay","year":"2022","journal-title":"Cells"},{"key":"B36","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"},{"key":"B37","doi-asserted-by":"publisher","first-page":"47754","DOI":"10.31083\/AP47754","article-title":"Development and validation of a machine learning-based predictive model for assessing the risk of comorbid depression in patients with asthma","volume":"26","author":"Nie","year":"2025","journal-title":"Alpha Psychiatry"},{"key":"B39","doi-asserted-by":"publisher","first-page":"8761","DOI":"10.1021\/acs.jmedchem.9b01101","article-title":"Interpretation of compound activity predictions from complex machine learning models using local approximations and shapley values","volume":"63","author":"Rodriguez-Perez","year":"2020","journal-title":"J. Med. Chem."},{"key":"B40","doi-asserted-by":"publisher","first-page":"e56922","DOI":"10.2196\/56922","article-title":"Machine learning-based prediction of neurodegenerative disease in patients with type 2 diabetes by derivation and validation in 2 independent Korean cohorts: model development and validation study","volume":"26","author":"Sang","year":"2024","journal-title":"J. Med. Internet Res."},{"key":"B41","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."},{"key":"B42","doi-asserted-by":"publisher","first-page":"1042996","DOI":"10.3389\/fcvm.2022.1042996","article-title":"Prediction model of obstructive sleep apnea-related hypertension: machine learning-based development and interpretation study","volume":"9","author":"Shi","year":"2022","journal-title":"Front. Cardiovasc Med."},{"key":"B43","doi-asserted-by":"publisher","first-page":"230","DOI":"10.1186\/s12911-023-02331-z","article-title":"Application and interpretation of machine learning models in predicting the risk of severe obstructive sleep apnea in adults","volume":"23","author":"Shi","year":"2023","journal-title":"BMC Med. Inf. Decis. Mak."},{"key":"B44","doi-asserted-by":"publisher","first-page":"64","DOI":"10.1186\/s12874-019-0681-4","article-title":"Machine learning in medicine: a practical introduction","volume":"19","author":"Sidey-Gibbons","year":"2019","journal-title":"BMC Med. Res. Methodol."},{"key":"B45","doi-asserted-by":"publisher","first-page":"107043","DOI":"10.1016\/j.aap.2023.107043","article-title":"Prediction of severity of aviation landing accidents using support vector machine models","volume":"187","author":"Silagyi","year":"2023","journal-title":"Accid. Anal. Prev."},{"key":"B46","doi-asserted-by":"publisher","first-page":"3397","DOI":"10.1007\/s11517-024-03145-5","article-title":"Machine learning models' assessment: trust and performance","volume":"62","author":"Sousa","year":"2024","journal-title":"Med. Biol. Eng. Comput."},{"key":"B47","doi-asserted-by":"publisher","first-page":"334","DOI":"10.1016\/j.jtos.2017.05.003","article-title":"TFOS DEWS II epidemiology report","volume":"15","author":"Stapleton","year":"2017","journal-title":"Ocul. Surf."},{"key":"B48","doi-asserted-by":"publisher","first-page":"330","DOI":"10.1016\/j.clae.2021.02.010","article-title":"CLEAR - contact lens complications","volume":"44","author":"Stapleton","year":"2021","journal-title":"Cont. Lens Anterior Eye."},{"key":"B49","doi-asserted-by":"publisher","first-page":"284","DOI":"10.1016\/j.jtos.2017.04.001","article-title":"TFOS DEWS II sex, gender, and hormones report","volume":"15","author":"Sullivan","year":"2017","journal-title":"Ocul. Surf."},{"key":"B50","doi-asserted-by":"publisher","first-page":"20482","DOI":"10.1002\/cam4.6540","article-title":"Prediction model of ocular metastasis from primary liver cancer: machine learning-based development and interpretation study","volume":"12","author":"Sun","year":"2023","journal-title":"Cancer Med."},{"key":"B51","doi-asserted-by":"publisher","first-page":"809","DOI":"10.1109\/TNNLS.2015.2424995","article-title":"Extreme learning machine for multilayer perceptron","volume":"27","author":"Tang","year":"2016","journal-title":"IEEE Trans. Neural Netw. Learn Syst."},{"key":"B52","doi-asserted-by":"publisher","first-page":"846709","DOI":"10.3389\/fmed.2022.846709","article-title":"Questionnaire analysis on incidence and risk factors of dry eye in children from a myopia outpatient clinic","volume":"9","author":"Wang","year":"2022","journal-title":"Front. Med. (Lausanne)"},{"key":"B53","doi-asserted-by":"publisher","first-page":"274","DOI":"10.1016\/j.ebiom.2018.01.024","article-title":"Allergic conjunctivitis-induced retinal inflammation promotes myopia progression","volume":"28","author":"Wei","year":"2018","journal-title":"EBioMedicine"},{"key":"B54","doi-asserted-by":"publisher","first-page":"104438","DOI":"10.1016\/j.ebiom.2023.104438","article-title":"Development and multi-center validation of machine learning model for early detection of fungal keratitis","volume":"88","author":"Wei","year":"2023","journal-title":"EBioMedicine"},{"key":"B55","doi-asserted-by":"publisher","first-page":"1812","DOI":"10.1038\/s41433-025-03749-7","article-title":"Causal effects of allergic diseases on the risk of myopia: a two-sample Mendelian randomization study","volume":"39","author":"Wei","year":"2025","journal-title":"Eye (Lond)."},{"key":"B56","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1016\/j.ajo.2017.03.013","article-title":"Postoperative efficacy, predictability, safety, and visual quality of laser corneal refractive surgery: a network meta-analysis","volume":"178","author":"Wen","year":"2017","journal-title":"Am. J. Ophthalmol."},{"key":"B57","doi-asserted-by":"publisher","first-page":"539","DOI":"10.1016\/j.jtos.2017.05.001","article-title":"TFOS DEWS II diagnostic methodology report","volume":"15","author":"Wolffsohn","year":"2017","journal-title":"Ocul. Surf."},{"key":"B58","doi-asserted-by":"publisher","first-page":"213","DOI":"10.1016\/j.jtos.2023.04.004","article-title":"TFOS lifestyle: impact of the digital environment on the ocular surface","volume":"28","author":"Wolffsohn","year":"2023","journal-title":"Ocul. Surf."},{"key":"B38","unstructured":"Ageing and health\n          \n          \n          2022"},{"key":"B59","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.ajo.2021.12.008","article-title":"Performances of machine learning in detecting glaucoma using fundus and retinal optical coherence tomography images: a meta-analysis","volume":"237","author":"Wu","year":"2022","journal-title":"Am. J. Ophthalmol."},{"key":"B60","doi-asserted-by":"publisher","first-page":"3744","DOI":"10.1002\/cam4.5060","article-title":"Using machine learning for mortality prediction and risk stratification in atezolizumab-treated cancer patients: integrative analysis of eight clinical trials","volume":"12","author":"Wu","year":"2023","journal-title":"Cancer Med."},{"key":"B61","doi-asserted-by":"publisher","first-page":"3107","DOI":"10.1111\/cas.16276","article-title":"Uveal melanoma distant metastasis prediction system: a retrospective observational study based on machine learning","volume":"115","author":"Wu","year":"2024","journal-title":"Cancer Sci."},{"key":"B62","doi-asserted-by":"publisher","first-page":"1541304","DOI":"10.3389\/fmed.2025.1541304","article-title":"Relationship between myopia and diagnosis rates of dry eye disease and related indicators: a systematic review and meta-analysis","volume":"12","author":"Wu","year":"2025","journal-title":"Front. Med. (Lausanne)"},{"key":"B63","doi-asserted-by":"publisher","first-page":"218","DOI":"10.1097\/OPX.0000000000001998","article-title":"Epidemiology and burden of astigmatism: a systematic literature review","volume":"100","author":"Zhang","year":"2023","journal-title":"Optom. Vis. Sci."},{"key":"B64","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1007\/s12016-025-09094-7","article-title":"Inflammation and immune pathways in myopia: an overview on pathomechanisms and treatment prospects","volume":"68","author":"Zhang","year":"2025","journal-title":"Clin. Rev. Allergy Immunol."},{"key":"B65","doi-asserted-by":"publisher","first-page":"785901","DOI":"10.3389\/fmed.2021.785901","article-title":"Mean tear-film lipid layer thickness and video display terminal time as risk factors for abnormal blinking in children","volume":"8","author":"Zhao","year":"2021","journal-title":"Front. Med. (Lausanne)"},{"key":"B66","doi-asserted-by":"publisher","first-page":"e38674","DOI":"10.1016\/j.heliyon.2024.e38674","article-title":"Relationship between dry eye disease and myopia: a systematic review and meta-analysis","volume":"10","author":"Zou","year":"2024","journal-title":"Heliyon"}],"container-title":["Frontiers in Cell and Developmental Biology"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fcell.2026.1770427\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T05:20:39Z","timestamp":1775712039000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fcell.2026.1770427\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,9]]},"references-count":66,"alternative-id":["10.3389\/fcell.2026.1770427"],"URL":"https:\/\/doi.org\/10.3389\/fcell.2026.1770427","relation":{},"ISSN":["2296-634X"],"issn-type":[{"value":"2296-634X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4,9]]},"article-number":"1770427"}}