{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T22:08:58Z","timestamp":1791842938883,"version":"4.3.4"},"reference-count":39,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T00:00:00Z","timestamp":1785110400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"},{"start":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T00:00:00Z","timestamp":1785110400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Acta Ophthalmologica"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    This systematic review and meta\u2010analysis evaluates the performance of artificial intelligence (AI)\u2010based models for predicting the onset and progression of refractive error (RE) in children and adolescents and quantitatively synthesizes their prediction accuracy. The study was preregistered in the PROSPERO database (CRD420251075160) and conducted in accordance with PRISMA guidelines. MEDLINE (via PubMed), Web of Science and Scopus were searched without time restrictions. Eligible studies involved children and adolescents (\u226418\u2009years) and applied AI\u2010based technologies to predict the onset or progression of RE, using non\u2010image\u2010based input data. To evaluate the prediction accuracy of the included studies, a meta\u2010analysis was performed. Quality assessment was conducted using the PROBAST+AI tool. Sixteen studies were included in the analysis. All studies evaluated myopia, two additionally addressed hyperopia and none focused on astigmatism. Most models predicted continuous SE values across the refractive spectrum, whereas a subset focused on classification\u2010based outcomes, such as myopia onset or progression. Included studies used diverse input data, including age, gender and parental myopia. Eight studies comprising 18 independent evaluations were included in the meta\u2010analysis. The pooled root\u2010mean\u2010squared error (RMSE) for spherical equivalent prediction was 0.50 D (95% confidence intervals: 0.37\u20130.62). Between\u2010study heterogeneity was substantial (\n                    <jats:italic>\u03c4<\/jats:italic>\n                    <jats:sup>2<\/jats:sup>\n                    \u2009=\u20090.0695,\n                    <jats:italic>I<\/jats:italic>\n                    <jats:sup>2<\/jats:sup>\n                    \u2009=\u2009100%), indicating major differences across models. This high heterogeneity reflects substantial differences in study populations, prediction targets and horizons, model architectures and validation strategies across included studies, and therefore, the pooled estimate should be interpreted as an average across diverse settings rather than a directly generalizable performance measure. Leave\u2010one\u2010out sensitivity analyses demonstrated that no single study materially influenced the pooled effect. Across all iterations, RMSE estimates ranged narrowly from 0.48 to 0.52 D, with confidence intervals overlapping the main analysis. The studies' quality assessment showed mostly low concern, apart from the analysis domain, in which 43.8% of studies were rated high risk. AI models using non\u2010image\u2010based clinical data demonstrate moderate accuracy for predicting paediatric RE onset and progression. However, substantial methodological heterogeneity and limited external validation indicate that standardized development and validation frameworks are required before clinical implementation.\n                  <\/jats:p>","DOI":"10.1111\/aos.70207","type":"journal-article","created":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T20:16:18Z","timestamp":1785183378000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Artificial intelligence prediction algorithms for refractive error onset and progression in children and adolescents: A systematic review and meta\u2010analysis"],"prefix":"10.1111","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-7706-4654","authenticated-orcid":false,"given":"Athanasia","family":"Sandali","sequence":"first","affiliation":[{"name":"Postgraduate Program in \u2018Ocular Surgery\u2019, School of Medicine Aristotle University of Thessaloniki  Thessaloniki Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anna","family":"Nikolaidou","sequence":"additional","affiliation":[{"name":"Institute for Ophthalmic Research University of T\u00fcbingen  T\u00fcbingen Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Theodora","family":"Gianni","sequence":"additional","affiliation":[{"name":"Department of Ophthalmology \u2018Aghia Sophia\u2019 Children's Hospital  Athens Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5805-105X","authenticated-orcid":false,"given":"Andreas","family":"Katsimpris","sequence":"additional","affiliation":[{"name":"Princess Alexandra Eye Pavilion University of Edinburgh  Edinburgh UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6439-9282","authenticated-orcid":false,"given":"Ioannis D.","family":"Apostolopoulos","sequence":"additional","affiliation":[{"name":"Artificial Intelligence, Computational Methods and Technological Applications (ACTA) Lab University of Thessaly  Larisa Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lampros","family":"Lamprogiannis","sequence":"additional","affiliation":[{"name":"Ophthalmica Institute of Ophthalmology and Microsurgery  Thessaloniki Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-3679-8807","authenticated-orcid":false,"given":"Eirini","family":"Maliagkani","sequence":"additional","affiliation":[{"name":"1st Department of Ophthalmology National and Kapodistrian University of Athens  Athens 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