ArticleNPJ digital medicine2022
Continuous monitoring of surgical bimanual expertise using deep neural networks in virtual reality simulation.
Article in NPJ digital medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 17 papers, 2 of them syntheses that pooled it.
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.
Effect of Intelligent Tutor Induced Pausing on Learning Simulated Surgical Skills Among Medical Students: A Randomized Controlled Trial
Effect of Music on Surgical Performance During Artificial Intelligence-Based Simulation Training: A Randomized Controlled Trial
Who cites it
17 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Deep learning in neurosurgery: a systematic literature review with a structured analysis of applications across subspecialties.Frontiers in neurology · 2025Pooled it
- Neurosurgical skills analysis by machine learning models: systematic review.Neurosurgical review · 2023Pooled it
- Real-Time multifaceted artificial intelligence vs In-Person instruction in teaching surgical technical skills: a randomized controlled trial.Scientific reports · 2024Trial
- AI in Surgical Curriculum Design and Unintended Outcomes for Technical Competencies in Simulation Training.JAMA network open · 2023Trial
- Review
- The future of robotic surgery in the age of artificial intelligence.Nature reviews. Urology · 2026Review
- Artificial Intelligence in Minimally Invasive and Robotic Gastrointestinal Surgery: Major Applications and Recent Advances.Journal of personalized medicine · 2026Review
- The Evolving Role of AI in Simulation-Based Medical Education: A Narrative Review.Advances in medical education and practice · 2026Review
- Transforming Surgical Training With AI Techniques for Training, Assessment, and Evaluation: Scoping Review.Journal of medical Internet research · 2025Article
- Virtual reality-augmented differentiable simulations for digital twin applications in surgical planning.Scientific reports · 2025Article
- Artificial Intelligence and Plastic Surgery Resident Education.Plastic and reconstructive surgery. Global open · 2025Article
- Analyzing Usage of the Metaverse by Associations of Patients With Prostate Cancer During the 2023 Blue Ribbon Campaign: Cross-Sectional Survey Study.Journal of medical Internet research · 2025Article
- A Symbolic AI Approach to Medical Training.Journal of medical systems · 2025Article
- Virtual reality-based surgical planning simulator for tumorous resection in FreeForm Modeling: an illustrative case of clinical teaching.Quantitative imaging in medicine and surgery · 2024Article
- Metaverse Wearables for Immersive Digital Healthcare: A Review.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Review
- Investigating and acquiring motor expertise using virtual reality.Journal of neurophysiology · 2023Review
- The digital transformation of surgery.NPJ digital medicine · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In procedural-based medicine, the technical ability can be a critical determinant of patient outcomes. Psychomotor performance occurs in real-time, hence a continuous assessment is necessary to provide action-oriented feedback and error avoidance guidance. We outline a deep learning application, the Intelligent Continuous Expertise Monitoring System (ICEMS), to assess surgical bimanual performance at 0.2-s intervals. A long-short term memory network was built using neurosurgeon and student performance in 156 virtually simulated tumor resection tasks. Algorithm predictive ability was tested separately on 144 procedures by scoring the performance of neurosurgical trainees who are at different training stages. The ICEMS successfully differentiated between neurosurgeons, senior trainees, junior trainees, and students. Trainee average performance score correlated with the year of training in neurosurgery. Furthermore, coaching and risk assessment for critical metrics were demonstrated. This work presents a comprehensive technical skill monitoring system with predictive validation throughout surgical residency training, with the ability to detect errors.
Identifiers
What 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.