What question did this study set out to answer?

This review aims to assess the performance of artificial intelligence models in predicting the onset of myopia in youths.

Predicting the Onset of Myopia in Children and Adolescents Using Artificial Intelligence: A Systematic Review and Meta-analysis

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Systematic review evaluates AI models' ability to predict myopia onset in children and adolescents, suggesting further research is needed.

This review aims to assess the performance of artificial intelligence models in predicting the onset of myopia in youths.
Systematic review and meta-analysis of studies using AI to predict myopia onset, searched through multiple databases until January 2026.
Pooled area under the curve (AUC) calculated using a random-effects model with risk of bias assessed by PROBAST+AI.
Seven studies with 24 models were analyzed, showing a pooled AUC of 0.95 for optimal models at one-year follow-up.
Traditional machine learning and deep learning models showed comparable discrimination, with AUCs of 0.85 and 0.86 respectively.
High risk of bias and prominent heterogeneity in findings were observed, indicating uncertainties in clinical utility.

Wang et al. (2026) studied this question.

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Systematic review evaluates AI models' ability to predict myopia onset in children and adolescents, suggesting further research is needed.