Artificial Intelligence in Pediatric Surgery—From Vision to Clinical Reality

Artificial intelligence (AI) has rapidly evolved from a promising concept to a transformative force in modern medicine. In radiology, pathology, oncology, and adult surgical care, AI and machine learning (ML) models are already reshaping diagnostics, decision-making, and patient outcomes. In addition to computer vision-based models, natural language processing (NLP) technologies are beginning to support documentation, guideline adherence, and communication in clinical workflows. Pediatric surgery, with its unique challenges of small patient populations, complex anatomy, and highly specialized procedures, is now entering this new era of innovation. AI-related publications in surgery have grown exponentially in recent years, and with regulation now taking shape, this is the moment for pediatric surgery to claim its place at the forefront of the transformation.

This special edition of the European Journal of Pediatric Surgery brings together leading experts to provide an overview of the state of AI in our field. ElSayed et al[1] outline the latest developments in general pediatric surgery, mapping out where ML-based models are already applied and where unmet needs persist. Esposito et al[2] explore the role of AI in robotic-assisted pediatric surgery, highlighting both the present possibilities and the future directions of intelligent robotic systems. Gnatzy et al[3] provide a comprehensive review of AI applications across the entire perioperative spectrum, from diagnostics and preoperative planning to intraoperative support and postoperative risk stratification. Verhoeven et al[4] take on one of the most pressing challenges in this domain: Explainability, ethics, and the urgent necessity for robust benchmarks to ensure safe, equitable, and trustworthy deployment of AI systems. Finally, Colunga et al[5] shed light on the practical side of “smart surgery,” demonstrating how tools like ChatGPT and other AI-powered NLP systems can simplify daily routines and augment the surgeon's workflow.

Taken together, these contributions provide both a snapshot of the current landscape and a framework for future research. While the opportunities are considerable, we must ensure transparency, rigorous validation, and a commitment to patient safety. The future of our specialty will not be defined by technology alone, but by how thoughtfully we integrate it into the care of our young patients.

We invite our readers to engage critically with the insights presented in this special issue, and to join in shaping a future where AI enhances—not replaces—the art and science of pediatric surgery.

Publication History

Received: 03 September 2025

Accepted: 13 September 2025

Article published online:
11 December 2025

• References

• 1 Elsayed H, Singer G, Till T, Till H. Latest developments in artificial intelligence and machine learning models in general pediatric surgery. Eur J Pediatr Surg Published online September 5, 2025;
• 2 Esposito C, Di MentoC, Del ConteF. et al. AI in robotic-assisted pediatric surgery: current applications and future directions. Eur J Pediatr Surg . Published online October 27, 2025;
• 3 Gnatzy R, Feng X, Graefe D, Deffaa OJ, Lacher M. Artificial Intelligence in Pediatric Surgery: From Diagnostics and Preoperative Planning to Risk Stratification: A Comprehensive Review of Current Applications. Eur J Pediatr Surg . Published online November 28, 2025;
• 4 Verhoeven R, Bouisaghouane W, Hulscher JB. Explainable AI: ethical frameworks, bias, and the necessity for benchmarks. Eur J Pediatr Surg . Published online September 23, 2025;
• 5 Tinajero CA. The pediatric surgeon's AI toolbox: how large language models like ChatGPT are simplifying practice and expanding global access. Eur J Pediatr Surg . Published online October 14, 2025;