ArticleJAMA network open2024
Deep Learning Analysis of Surgical Video Recordings to Assess Nontechnical Skills.
Article in JAMA network open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
13 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Impact of surgical non-technical skills on clinical outcomes: systematic review.The British journal of surgery · 2025Pooled it
- Deep learning in neurosurgery: a systematic literature review with a structured analysis of applications across subspecialties.Frontiers in neurology · 2025Pooled it
- Artificial intelligence-supported segmentation of cardiac anatomy in open-heart surgery videos.Journal of robotic surgery · 2026Article
- Heart Rate Variability and Body Motion as Digital Biomarkers of Task Workload During Military En Route Critical Care Simulations.Sensors (Basel, Switzerland) · 2026Article
- Video-based assessment identifies intraoperative predictors of clinically relevant POPF following minimally invasive distal pancreatectomy.Surgical endoscopy · 2026Article
- From innovation to implementation: Addressing the AI adoption gap in cardiac surgery.American heart journal plus : cardiology research and practice · 2026Review
- Identifying novel indicators of non-technical skills derived from operative video annotation.The British journal of surgery · 2026Article
- A function-based framework for AI-amplified, data-driven healthcare simulation research.Advances in simulation (London, England) · 2026Article
- Towards accurate and interpretable competency-based assessment: enhancing clinical competency assessment through multimodal AI and anomaly detection.NPJ digital medicine · 2026Article
- A Qualitative Exploratory Study of Patient Safety and Nurses' Body Awareness Using Motion-Capture-Linked Avatars.Journal of nursing management · 2026Article
- Early Detection of Cystoid Macular Edema in Retinitis Pigmentosa Using Longitudinal Deep Learning Analysis of OCT Scans.Diagnostics (Basel, Switzerland) · 2025Article
- Consensus on Key Attributes of Cardiac Surgeons' Intraoperative Performance.Journal of surgical education · 2025Article
- Augmented Reality in Enhancing Operating Room Crisis Checklist Adherence: Randomized Comparative Efficacy Study.JMIR XR and spatial computing · 2025Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Importance: Assessing nontechnical skills in operating rooms (ORs) is crucial for enhancing surgical performance and patient safety. However, automated and real-time evaluation of these skills remains challenging. Objective: To explore the feasibility of using motion features extracted from surgical video recordings to automatically assess nontechnical skills during cardiac surgical procedures. Design, Setting, and Participants: This cross-sectional study used video recordings of cardiac surgical procedures at a tertiary academic US hospital collected from January 2021 through May 2022. The OpenPose library was used to analyze videos to extract body pose estimations of team members and compute various team motion features. The Non-Technical Skills for Surgeons (NOTSS) assessment tool was employed for rating the OR team's nontechnical skills by 3 expert raters. Main Outcomes and Measures: NOTSS overall score, with motion features extracted from surgical videos as measures. Results: A total of 30 complete cardiac surgery procedures were included: 26 (86.6%) were on-pump coronary artery bypass graft procedures and 4 (13.4%) were aortic valve replacement or repair procedures. All patients were male, and the mean (SD) age was 72 (6.3) years. All surgical teams were composed of 4 key roles (attending surgeon, attending anesthesiologist, primary perfusionist, and scrub nurse) with additional supporting roles. NOTSS scores correlated significantly with trajectory (r = 0.51, P = .005), acceleration (r = 0.48, P = .008), and entropy (r = -0.52, P = .004) of team displacement. Multiple linear regression, adjusted for patient factors, showed average team trajectory (adjusted R2 = 0.335; coefficient, 10.51 [95% CI, 8.81-12.21]; P = .004) and team displacement entropy (adjusted R2 = 0.304; coefficient, -12.64 [95% CI, -20.54 to -4.74]; P = .003) were associated with NOTSS scores. Conclusions and Relevance: This study suggests a significant link between OR team movements and nontechnical skills ratings by NOTSS during cardiac surgical procedures, suggesting automated surgical video analysis could enhance nontechnical skills assessment. Further investigation across different hospitals and specialties is necessary to validate these findings.
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Registered trials
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