ArticleAnnals of surgery2019
Modeling Surgical Technical Skill Using Expert Assessment for Automated Computer Rating.
Article in Annals of surgery, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.
What it found
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The trial behind it
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Who cites it
31 citing papers in PubMed, 1 synthesis or guideline pooled it, 82 citations in OpenAlex.
- The Advent of Artificial Intelligence into Cardiac Surgery: A Systematic Review of Our Understanding.Brazilian journal of cardiovascular surgery · 2024Pooled it
- Assessment of open surgery suturing skills via markerless hand tracking: a multistage approach using 3D hand skeleton and kinematic metrics.International journal of computer assisted radiology and surgery · 2026Article
- Artificial intelligence-based approaches to augmenting and automating surgical training.BJU international · 2026Review
- The first reported case using real-time artificial intelligence with single-port robotics for colorectal surgery.Surgical endoscopy · 2026Article
- Quantitative Analysis of Instrument Motion Paths in Cataract Surgery across a Resident's Training.Ophthalmology science · 2026Article
- An Egocentric Life-Saving Interventional Procedure Dataset of Actions, Medical Questions, Maneuvers and Tools.Scientific data · 2025Article
- Automatic surgical skill assessment using a task classification model in laparoscopic sigmoidectomy.Surgical endoscopy · 2025Article
- Analyzing Procedural Time and Its Relationship to Performance in Microsurgical Training: A Pilot Study.Cureus · 2025Article
- Use of artificial intelligence in the analysis of digital videos of invasive surgical procedures: scoping review.BJS open · 2025Article
- Artificial Intelligence in Medical Education: a Scoping Review of the Evidence for Efficacy and Future Directions.Medical science educator · 2025Review
- Article
- Change in economy of ultrasound probe motion among general medicine trainees.The ultrasound journal · 2024Article
- Automatic surgical phase recognition-based skill assessment in laparoscopic distal gastrectomy using multicenter videos.Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association · 2024Article
- TAToo: vision-based joint tracking of anatomy and tool for skull-base surgery.International journal of computer assisted radiology and surgery · 2023Article
- An Automated Skill Assessment Framework Based on Visual Motion Signals and a Deep Neural Network in Robot-Assisted Minimally Invasive Surgery.Sensors (Basel, Switzerland) · 2023Article
- Automatic purse-string suture skill assessment in transanal total mesorectal excision using deep learning-based video analysis.BJS open · 2023Article
- Automated Capture of Intraoperative Adverse Events Using Artificial Intelligence: A Systematic Review and Meta-Analysis.Journal of clinical medicine · 2023Review
- Robot-assisted ex vivo neobladder reconstruction: preliminary results of surgical skill evaluation.International journal of computer assisted radiology and surgery · 2022Article
- Detection of blood stains using computer vision-based algorithms and their association with postoperative outcomes in thoracoscopic lobectomies.European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery · 2022Article
- Artificial Intelligence in Colorectal Cancer Surgery: Present and Future Perspectives.Cancers · 2022Review
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
objectiveComputer vision was used to predict expert performance ratings from surgeon hand motions for tying and suturing tasks. SUMMARY BACKGROUND DATA: Existing methods, including the objective structured assessment of technical skills (OSATS), have proven reliable, but do not readily discriminate at the task level. Computer vision may be used for evaluating distinct task performance throughout an operation.
methodsOpen surgeries was videoed and surgeon hands were tracked without using sensors or markers. An expert panel of 3 attending surgeons rated tying and suturing video clips on continuous scales from 0 to 10 along 3 task measures adapted from the broader OSATS: motion economy, fluidity of motion, and tissue handling. Empirical models were developed to predict the expert consensus ratings based on the hand kinematic data records.
resultsThe predicted versus panel ratings for suturing had slopes from 0.73 to 1, and intercepts from 0.36 to 1.54 (Average R2 = 0.81). Predicted versus panel ratings for tying had slopes from 0.39 to 0.88, and intercepts from 0.79 to 4.36 (Average R2 = 0.57). The mean square error among predicted and expert ratings was consistently less than the mean squared difference among individual expert ratings and the eventual consensus ratings.
conclusionsThe computer algorithm consistently predicted the panel ratings of individual tasks, and were more objective and reliable than individual assessment by surgical experts.
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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.