Clinical Report: Bibliometric Trends of AI in Gastrointestinal Surgery (2015-2025)
Overview
This bibliometric analysis evaluates global research trends on artificial intelligence (AI) applications in gastrointestinal surgery over the past decade. It identifies key publication patterns, research hotspots, and future directions, highlighting AI's growing role in diagnosis, surgical assistance, and risk prediction.
Background
Gastrointestinal surgery has evolved significantly from ancient practices to modern minimally invasive and robotic techniques, improving patient outcomes and recovery. Despite advances, challenges remain in preoperative diagnostics, intraoperative precision, and postoperative management. Artificial intelligence technologies, including deep learning and robotic systems, are increasingly integrated to enhance diagnostic accuracy, surgical safety, and personalized care. However, research in this interdisciplinary field is scattered, necessitating a comprehensive bibliometric evaluation to map progress and guide future investigations.
Data Highlights
Parameter
Details
Database
Web of Science Core Collection (SCIE)
Search Period
July 13, 2015 – July 13, 2025
Document Types
Monographs and Review Articles (English only)
Search Terms
Keywords related to AI (CNN, Deep Learning, AI) and gastrointestinal surgeries (colon, rectal, gastric cancers and surgeries)
Dual independent data extraction with third-party adjudication for discrepancies
Key Findings
AI-driven deep learning algorithms significantly improve diagnostic accuracy for gastrointestinal endoscopic lesions.
Robotic surgery systems, such as the da Vinci platform, enhance surgical precision and safety through AI-enabled 3D imaging.
Bibliometric data reveal increasing publication volume and citation impact in AI applications within gastrointestinal surgery over the last decade.
Research hotspots include AI-assisted diagnosis, surgical assistance, and postoperative risk prediction.
Global research contributions are mapped across countries, institutions, and authors, highlighting collaborative networks.
Current literature remains fragmented, underscoring the need for systematic analyses to consolidate knowledge and guide future research.
Clinical Implications
Clinicians should recognize the expanding role of AI technologies in improving diagnostic and surgical outcomes in gastrointestinal surgery. Integration of AI tools can aid in overcoming subjective biases in imaging interpretation and enhance intraoperative decision-making. Awareness of evolving research trends can inform evidence-based adoption and foster multidisciplinary collaboration.
Conclusion
This bibliometric analysis underscores the rapid growth and diversification of AI applications in gastrointestinal surgery, emphasizing its potential to transform clinical practice. Continued systematic research and collaboration are essential to fully realize AI's benefits in precision surgical care.
References
Myrseth et al. 2020 -- Robot-assisted rectal resection safety and feasibility
Enhanced Recovery After Surgery (ERAS) protocols -- Colorectal surgery postoperative care
AI in gastrointestinal endoscopy -- Diagnostic accuracy improvements
Bibliometrics in medical research -- Assessing publication trends
