Surgical Education

AI-powered tools that automatically document clinical conversations are being adopted rapidly in outpatient settings but have not been evaluated in hospital wards. Existing tools use audio recording only, which cannot capture physical examination findings, procedural observations, or clinical safety behaviours - elements of a ward round that are visible but not audible. This study evaluates an ambient audio-visual (AV) capture system - BlackFrame - that uses both microphone and camera to generate accurate clinical documentation and structured educational feedback in a real inpatient surgical ward setting. Medical students and doctors in training participate in supervised ward round encounters with consenting adult inpatients. The BlackFrame AI platform generates: (a) a structured draft clinical note for the supervising clinician to review and countersign before any use in the patient record; and (b) formative feedback for the trainee, delivered within 30 minutes, covering clinical communication, examination technique, and documentation quality. The study measures whether AI-generated feedback improves trainee clinical performance over a placement, how much documentation time is saved, and whether the system is acceptable to patients and clinicians. No AI-generated text enters the patient record without explicit clinician review and sign-off. All participation is voluntary.

Neurosurgery is a high-stakes surgical specialty where errors can result in significant morbidity. The amount of force applied simultaneously on the brain with multiple different instruments during complex neurosurgical procedures is a critical safety metric that, to the investigators' knowledge, has not been previously measured in a realistic operative environment. The investigators have therefore developed a simulation platform integrating an ex vivo calf brain and a 3D-printed skull model attached to a force sensor capable of capturing real-time forces applied to the brain. A case series study will be conducted to evaluate the pattern of force applied. Medical students, neurosurgical residents, and staff neurosurgeons from McGill University will be recruited to perform subpial resections using our ex vivo calf brain simulation platform. The forces applied by the microscissors, bipolar forceps, and ultrasonic aspirator onto the brain will be captured. This study aims to demonstrate the spectrum of force applied during a neurosurgical procedure using an ex vivo calf brain model.

Neurosurgery is a high-stakes surgical specialty where errors can result in significant patient mortality and morbidity. The amount of force applied on the brain simultaneously by the multiple different instruments during complex neurosurgical procedures is a critical safety metric that, to the investigators' knowledge, has not been previously measured in a realistic operative environment. The investigators have therefore developed a simulation platform integrating an ex vivo calf brain and a 3D-printed skull model attached to a force sensor capable of capturing real-time forces applied to the brain. A cross-sectional case series study will be conducted to evaluate the validity of the system. Medical students, neurosurgical residents, neurosurgical fellows, and staff neurosurgeons from four Quebec institutions will be recruited to perform three simulated subpial resections each using our ex vivo calf brain simulation platform. The forces applied by the microscissors, bipolar forceps, and ultrasonic aspirator onto the brain will be captured along with kinematic data. This study aims to establish the face, content, construct, and convergent validity of this ex vivo calf brain force detection system.

This study aims to improve basic laparoscopic and thoracoscopic skills in thoracic surgery residents and rotating surgical residents through a structured simulation-based training program. Participants will complete hands-on practice sessions using box trainers, artificial models, and bovine tissues in a controlled, non-patient setting. Before and after the training, participants will complete self-assessment surveys and a standardized technical skills evaluation (OSATS). The study will compare these results to measure changes in technical performance, confidence, and learning needs. No real patients, live animals, or clinical procedures are involved, and there are no expected medical risks. The goal of this study is to determine whether structured simulation training is effective, practical, and acceptable for surgical education, and whether it can support safer transition to real operating room experience in the future.

This randomized controlled trial aims to compare the effectiveness of a digital gamification-based training method and a traditional training method on instrument table layout skills in total hip replacement surgery. Nursing students will be randomly assigned to either a game-based learning group or a control group receiving conventional education. The primary outcome is the accuracy of surgical instrument placement. The study will be conducted at Bozok University in Turkey.

the metaverse system applied to the training of wound location selection for singleport thoracoscopic surgery. The experimental design is two groups of 40 computer tomography located superficially less than 2 cm lung nodule patients, one group uses the metaverse system to let resident physicians simulate the wound position on the digital twin organs of each patient, and the other group does not use it. The investigators will evaluate the surgeon's satisfaction with the surgical wound position and urgicalrelated results (such as surgery time, blood loss, etc.). The investigators expect that the system will help improve the appropriateness of resident physicians' choice of wound location for high-difficulty single-port thoracoscopic surgery, help them cross the first threshold necessary to familiarize themselves with the surgery faster, and accelerate learning.

The goal of this clinical trial is to learn if patient specific virtual reality (VR) simulations can be used for surgical orthopaedic education in resident and fellow physician populations.