ArticleSurgical endoscopy2023
What is the educational value and clinical utility of artificial intelligence for intraoperative and postoperative video analysis? A survey of surgeons and trainees.
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 12 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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
12 citing papers in PubMed.
- A Conceptual Model for Embedding Automated Assessments in Graduate Medical Education.Journal of graduate medical education · 2026Article
- Optimizing AI implementation for surgery: recommendations for infrastructure and deployment in the operating room.NPJ digital medicine · 2026Article
- Development of a stakeholder-informed framework for the implementation of surgical sabermetrics to enhance training and education.The British journal of surgery · 2026Article
- LungSurg: A Generative AI System for Segmentation and Phase Classification in Thoracoscopic Lobectomy.MedComm · 2026Article
- Quantitative Analysis of Instrument Motion Paths in Cataract Surgery across a Resident's Training.Ophthalmology science · 2026Article
- Artificial intelligence assisted operative anatomy recognition in endoscopic pituitary surgery.NPJ digital medicine · 2024Article
- Article
- Development, deployment and scaling of operating room-ready artificial intelligence for real-time surgical decision support.NPJ digital medicine · 2024Article
- Risk Management and Patient Safety in the Artificial Intelligence Era: A Systematic Review.Healthcare (Basel, Switzerland) · 2024Review
- Review
- Review
- Practical Efficacy of the Mobile Video Feedback Method in Teaching Clinical Abscess Incision and Drainage Skills.Journal of medical education and curricular developmentArticle
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionSurgical complications often occur due to lapses in judgment and decision-making. Advances in artificial intelligence (AI) have made it possible to train algorithms that identify anatomy and interpret the surgical field. These algorithms can potentially be used for intraoperative decision-support and postoperative video analysis and feedback. Despite the very early success of proof-of-concept algorithms, it remains unknown whether this innovation meets the needs of end-users or how best to deploy it. This study explores users' opinion on the value, usability and design for adapting AI in operating rooms.
methodsA device-agnostic web-accessible software was developed to provide AI inference either (1) intraoperatively on a live video stream (synchronous mode), or (2) on an uploaded video or image file (asynchronous mode) postoperatively for feedback. A validated AI model (GoNoGoNet), which identifies safe and dangerous zones of dissection during laparoscopic cholecystectomy, was used as the use case. Surgeons and trainees performing laparoscopic cholecystectomy interacted with the AI platform and completed a 5-point Likert scale survey to evaluate the educational value, usability and design of the platform.
resultsTwenty participants (11 surgeons and 9 trainees) evaluated the platform intraoperatively (n = 10) and postoperatively (n = 11). The majority agreed or strongly agreed that AI is an effective adjunct to surgical training (81%; neutral = 10%), effective for providing real-time feedback (70%; neutral = 20%), postoperative feedback (73%; neutral = 27%), and capable of improving surgeon confidence (67%; neutral = 29%). Only 40% (neutral = 50%) and 57% (neutral = 43%) believe that the tool is effective in improving intraoperative decisions and performance, or beneficial for patient care, respectively. Overall, 38% (neutral = 43%) reported they would use this platform consistently if available. The majority agreed or strongly agreed that the platform was easy to use (81%; neutral = 14%) and has acceptable resolution (62%; neutral = 24%), while 30% (neutral = 20%) reported that it disrupted the OR workflow, and 20% (neutral = 0%) reported significant time lag. All respondents reported that such a system should be available "on-demand" to turn on/off at their discretion.
conclusionsMost found AI to be a useful tool for providing support and feedback to surgeons, despite several implementation obstacles. The study findings will inform the future design and usability of this technology in order to optimize its clinical impact and adoption by end-users.
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37697116What OpenQuestion holds
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.