ReviewTranslational pediatrics2026
Artificial intelligence in congenital heart surgery: a scoping review and primer for surgeons.
Review in Translational pediatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
6 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Background: Congenital heart surgery (CHS) encompasses a wide spectrum of complex cardiac defects, many of which demand specialised perioperative management and tailored surgical planning. Artificial intelligence (AI), including machine learning (ML), is gaining prominence as a tool to optimise clinical decision-making and achieve better outcomes. This scoping review aims to map and summarise the existing applications of AI modalities in CHS. Methods: A comprehensive search of MEDLINE, Embase, and Web of Science was performed, combining terms for AI with terms for congenital heart disease and surgery. Results: A total of 2,871 articles were retrieved from the search, of which 93 studies were included. The majority of studies focused on outcome prediction and imaging-based applications. Smaller proportions addressed decision-making and data augmentation, omics integration, benchmarking and quality improvement. The majority of studies examined heterogeneous congenital heart disease (CHD) populations, with tetralogy of Fallot (TOF) and single ventricle physiology most frequently represented. Conclusions: AI applications in CHS are rapidly expanding across diverse domains, with early studies showing encouraging potential to support diagnostics, guide surgical decision-making, and improve perioperative outcomes. However, most models remain in the preliminary stage with limited external validation. Emerging advances in AI may further accelerate progress, but careful evaluation and integration are essential to translate this promise into tangible clinical benefits.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.