Artificial intelligence for patent ductus arteriosus—a systematic review
Artificial intelligence shows feasibility for supporting PDA risk stratification, diagnosis, severity assessment, and prediction of treatment-related outcomes. However, current applications remain in early, pilot-stage development and are not yet suitable for clinical implementation. Future work should prioritize clinically meaningful tasks, scientifically rigorous and bias-aware methodologies, larger and more representative cohorts, and systematic external validation. Fairness, explainability, and reproducibility must be addressed to support translation. Continued methodological refinement and clinical grounding will be key to unlocking the potential of these technologies for this highly vulnerable patient population in the future.
Authors
- Sarah Elizabeth Long
- Steffen Oeltze‐Jafra (ORCID: https://orcid.org/0000-0002-6962-9080)
- Philipp Beerbaum (ORCID: https://orcid.org/0000-0001-9090-0392)
- C. Peter
- Theodor Uden
Institutions
- Universitas Methodist Indonesia (ID)
- Medizinische Hochschule Hannover (DE)
Publication Details
- Journal
- Frontiers in Pediatrics
- Published
- 2026-01-30
- DOI
- https://doi.org/10.3389/fped.2026.1648943
- Primary Topic
- Cardiovascular Conditions and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Else Kröner-Fresenius-Stiftung
- Medizinischen Hochschule Hannover