ArticleGastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association2024
Automatic surgical phase recognition-based skill assessment in laparoscopic distal gastrectomy using multicenter videos.
Article in Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
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20 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.
- Artificial intelligence in the operating room: A systematic review of AI models for surgical phase, instruments and anatomical structure identification.Acta obstetricia et gynecologica Scandinavica · 2025Pooled it
- Automated surgical phase recognition in pediatric laparoscopic fundoplication using deep learning: a retrospective video-based study.Surgical endoscopy · 2026Article
- Artificial intelligence-based phase recognition for workflow analysis in robotic choledochal cyst excision: a proof-of-concept study.Surgical endoscopy · 2026Article
- Machine Learning for Human-Autonomy Teaming in Surgical Skill Assessment: Scoping Review.JMIR AI · 2026Review
- AI-based assessment of surgical efficiency and exposure quality in laparoscopic distal gastrectomy using a phase recognition model.Surgical endoscopy · 2026Article
- Development of an Artificial Intelligence Platform for Surgical Tool Detection and Phase Recognition in Laparoscopic Distal Gastrectomy.Journal of gastric cancer · 2026Article
- Automated surgical phase recognition and analysis in single-incision laparoscopic cholecystectomy using artificial intelligence.Surgical endoscopy · 2026Article
- Machine learning-driven automated evaluation of surgical skills during laparoscopic distal gastrectomy based on blood pixel analysis.Surgical endoscopy · 2026Article
- Artificial Intelligence-Based Surgical Phase Analysis Enables Objective Assessment of Surgeon Skill in Robotic Distal Gastrectomy: A Multicenter Study.Annals of gastroenterological surgery · 2026Article
- Artificial Intelligence Applications in Gastric Cancer Surgery: Bridging Early Diagnosis and Responsible Precision Medicine.Journal of clinical medicine · 2026Review
- Artificial Intelligence in Minimally Invasive and Robotic Gastrointestinal Surgery: Major Applications and Recent Advances.Journal of personalized medicine · 2026Review
- Surgical video-based temporal action analysis algorithm and competency assessment in laparoscopic cholecystectomy: development and exploratory evaluation.Surgical endoscopy · 2026Article
- Renji endoscopic submucosal dissection video data set for Esophagus.Scientific data · 2025Article
- Artificial Intelligence in Gastrointestinal Surgery: A Systematic Review of Its Role in Laparoscopic and Robotic Surgery.Journal of personalized medicine · 2025Review
- Surgical skill assessment using an AI-based surgical phase recognition model for laparoscopic cholecystectomy.Surgical endoscopy · 2025Article
- Automated surgical action recognition and competency assessment in laparoscopic cholecystectomy: a proof-of-concept study.Surgical endoscopy · 2025Article
- Development and Evaluation of the Reliability and Validity of Video-Based Assessment Checklists of Nursing Skills via Chest-Mounted Cameras for Home-Visiting Nurses.Nursing research and practice · 2025Article
- Artificial intelligence based surgical support for experimental laparoscopic Nissen fundoplication.Frontiers in pediatrics · 2025Article
- Deep learning-based surgical step recognition for laparoscopic right-sided colectomy.Langenbeck's archives of surgery · 2024Article
- Laparoscopic distal gastrectomy skill evaluation from video: a new artificial intelligence-based instrument identification system.Scientific reports · 2024Article
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundGastric surgery involves numerous surgical phases; however, its steps can be clearly defined. Deep learning-based surgical phase recognition can promote stylization of gastric surgery with applications in automatic surgical skill assessment. This study aimed to develop a deep learning-based surgical phase-recognition model using multicenter videos of laparoscopic distal gastrectomy, and examine the feasibility of automatic surgical skill assessment using the developed model.
methodsSurgical videos from 20 hospitals were used. Laparoscopic distal gastrectomy was defined and annotated into nine phases and a deep learning-based image classification model was developed for phase recognition. We examined whether the developed model's output, including the number of frames in each phase and the adequacy of the surgical field development during the phase of supra-pancreatic lymphadenectomy, correlated with the manually assigned skill assessment score.
resultsThe overall accuracy of phase recognition was 88.8%. Regarding surgical skill assessment based on the number of frames during the phases of lymphadenectomy of the left greater curvature and reconstruction, the number of frames in the high-score group were significantly less than those in the low-score group (829 vs. 1,152, P < 0.01; 1,208 vs. 1,586, P = 0.01, respectively). The output score of the adequacy of the surgical field development, which is the developed model's output, was significantly higher in the high-score group than that in the low-score group (0.975 vs. 0.970, P = 0.04).
conclusionThe developed model had high accuracy in phase-recognition tasks and has the potential for application in automatic surgical skill assessment systems.
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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 OpenQuestion graph.