Artificial intelligence for patent ductus arteriosus—a systematic review

Introduction: Optimal management of patent ductus arteriosus (PDA) remains controversial. Complexity in severity appraisal, high-dimensional data, and the need for longitudinal, individualized assessment make PDA a compelling candidate for Artificial Intelligence (AI)-driven approaches. This systematic review evaluates AI research in the context of PDA, identifying strengths, limitations, and future directions. Methods: Following PRISMA 2020, databases were searched for peer-reviewed articles from January 1, 2010, to May 31, 2025. Eleven studies met inclusion criteria. Data on design, population, sources, AI methods, performance, validation, limitations, and explainability were extracted. Risk of bias was assessed using the Prediction model Risk of Bias Assessment Tool and Joanna Briggs Institute Critical Appraisal Checklist; reporting quality using the Minimum Information about Clinical AI Modeling checklist. Heterogeneity precluded meta-analysis; therefore findings were synthesized narratively. Results: = 1). Ten were retrospective; nine single-center, one multi-center, and one used a national registry. Sample sizes were mostly