ReviewTranslational pediatrics2026
AI in pediatric surgery: a narrative review.
Review in Translational pediatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
- Clinical translation of artificial intelligence in hypospadias: a systematic review and meta-analysis.Pediatric surgery international · 2026Pooled it
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and Objective: Artificial intelligence (AI) is transforming the medical field, including pediatric surgery, by enhancing diagnostic precision, surgical planning, intraoperative guidance, and postoperative care. Despite the increasing interest, a comprehensive understanding of AI's current applications and challenges in pediatric surgery is lacking. This narrative review aims to summarize current AI applications in pediatric surgery and evaluate their impact on clinical care, surgical training, and patient outcomes. Methods: A literature review was conducted in January 2025 using PubMed and Web of Science. The search terms were "artificial intelligence" and "pediatric surgery", restricted to English-language articles published from 2015 to 2025. After excluding studies on adult populations and unrelated specialties, 46 articles were selected for analysis. Key Content and Findings: The reviewed literature demonstrates AI's utility across the pediatric surgical spectrum. Most prominently, AI enhances diagnostic accuracy for conditions like appendicitis, necrotizing enterocolitis (NEC), Hirschsprung's disease (HD) and biliary atresia. AI also supports surgical planning via three-dimensional (3D) modeling, augments intraoperative navigation and skill assessment, and improves postoperative care through complication prediction and pain evaluation. Furthermore, AI tools facilitate caregiver education and emotional support. Nevertheless, limitations remain, including pediatric data scarcity, variability in model reporting, and unresolved ethical and legal concerns. Conclusions: AI holds great potential for transforming pediatric surgical care by improving accuracy, efficiency, and personalization. Future research should focus on generating robust pediatric datasets, validating tools in clinical settings, and integrating ethical frameworks. AI-human collaboration could reshape pediatric surgery and contribute meaningfully to patient care and policy development.
Indexed as
Identifiers
What Socratic holds
Registered trials
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.