ArticleSurgical endoscopy2023
A novel high accuracy model for automatic surgical workflow recognition using artificial intelligence in laparoscopic totally extraperitoneal inguinal hernia repair (TEP).
Article in Surgical endoscopy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 2 of them syntheses that pooled it.
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Who cites it
27 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- 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
- Machine learning, deep learning and hernia surgery. Are we pushing the limits of abdominal core health? A qualitative systematic review.Hernia : the journal of hernias and abdominal wall surgery · 2024Pooled it
- A novel artificial intelligence anatomical model for landmark recognition in endolaparoscopic totally extraperitoneal inguinal hernia repair.Surgical endoscopy · 2026Article
- Artificial intelligence in abdominal wall hernia surgery: clinical applications and translational readiness.Surgical endoscopy · 2026Review
- Artificial intelligence assessment of Parkland's grading scale in laparoscopic cholecystectomy: a step toward real-world outcome prediction.Updates in surgery · 2026Article
- AI-based disease severity grading predicts complications in laparoscopic appendectomy.Surgical endoscopy · 2026Article
- External validation and clinical readiness of intraoperative video AI in general surgery: a systematic review.Surgery today · 2026Review
- Development of a deep-learning model to detect free air on abdominal computed tomography for surgical decision support.International journal of surgery (London, England) · 2026Article
- Artificial intelligence in urology training Enhancing annotation, feedback, and evaluation in robotic, laparoscopic, and endoscopic surgery.Canadian Urological Association journal = Journal de l'Association des urologues du Canada · 2026Review
- Automated Operative Phase and Step Recognition in Vestibular Schwannoma Surgery: Development and Preclinical Evaluation of a Deep Learning Neural Network (IDEAL Stage 0).Neurosurgery · 2026Article
- Artificial-Intelligence-based Surgical Phase Recognition in Robot-Assisted Radical Prostatectomy and Cross-Surgeon Validation.Annals of surgical oncology · 2026Article
- Artificial Intelligence in Minimally Invasive and Robotic Gastrointestinal Surgery: Major Applications and Recent Advances.Journal of personalized medicine · 2026Review
- Deep learning-driven multi-hierarchical granularity integration for surgical scene understanding: experimental study.International journal of surgery (London, England) · 2026Article
- Application of machine learning and deep learning in the diagnosis and treatment of inguinal hernia: a narrative review.Frontiers in medicine · 2026Review
- Role of Robotic Surgery and Artificial Intelligence in the Management of Abdominal Wall Hernias: A Systematic Review.Cureus · 2025Review
- Artificial Intelligence in Gastrointestinal Surgery: A Systematic Review of Its Role in Laparoscopic and Robotic Surgery.Journal of personalized medicine · 2025Review
- Renji endoscopic submucosal dissection video data set for colorectal neoplastic lesions.Scientific data · 2025Article
- Use of artificial intelligence in the analysis of digital videos of invasive surgical procedures: scoping review.BJS open · 2025Article
- Using artificial intelligence to evaluate adherence to best practices in one anastomosis gastric bypass: first steps in a real-world setting.Surgical endoscopy · 2025Article
- Renji endoscopic submucosal dissection video data set for early gastric cancer.Scientific data · 2025Article
Corrections and comments
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Authors and funding
8 authors.
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No grant is acknowledged in the PubMed record.
Abstract
introductionArtificial intelligence and computer vision are revolutionizing the way we perceive video analysis in minimally invasive surgery. This emerging technology has increasingly been leveraged successfully for video segmentation, documentation, education, and formative assessment. New, sophisticated platforms allow pre-determined segments chosen by surgeons to be automatically presented without the need to review entire videos. This study aimed to validate and demonstrate the accuracy of the first reported AI-based computer vision algorithm that automatically recognizes surgical steps in videos of totally extraperitoneal (TEP) inguinal hernia repair.
methodsVideos of TEP procedures were manually labeled by a team of annotators trained to identify and label surgical workflow according to six major steps. For bilateral hernias, an additional change of focus step was also included. The videos were then used to train a computer vision AI algorithm. Performance accuracy was assessed in comparison to the manual annotations.
resultsA total of 619 full-length TEP videos were analyzed: 371 were used to train the model, 93 for internal validation, and the remaining 155 as a test set to evaluate algorithm accuracy. The overall accuracy for the complete procedure was 88.8%. Per-step accuracy reached the highest value for the hernia sac reduction step (94.3%) and the lowest for the preperitoneal dissection step (72.2%).
conclusionsThese results indicate that the novel AI model was able to provide fully automated video analysis with a high accuracy level. High-accuracy models leveraging AI to enable automation of surgical video analysis allow us to identify and monitor surgical performance, providing mathematical metrics that can be stored, evaluated, and compared. As such, the proposed model is capable of enabling data-driven insights to improve surgical quality and demonstrate best practices in TEP procedures.
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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 OpenQuestion graph.