Publications by authors named "B Dallemagne"
Purpose: We establish stepwise training program in which laparoscopic suturing is broken down to discrete steps. The purpose is to evaluate the learning outcomes of stepwise training program.
Materials And Methods: Volunteer participants were enrolled from medical students and surgical trainees.
Introduction: Gas leaks polluting the operating room are common in laparoscopy. Studies defining methods for sensitive leak characterisation and mechanical mitigation in real world settings are, however, lacking.
Methods: Mobile optical gas imagers (both a miniaturised Schlieren system and sensitive tripod-mounted near-infrared carbon dioxide camera (GF343, FLIR)) prospectively defined trocar-related gas leaks occurring either spontaneously or with instrumentation during planned laparoscopic surgery at three hospitals.
: Laparoscopic cholecystectomy (LC) is one of the most performed surgeries worldwide. Procedure difficulty and patient outcomes depend on several factors which are not considered in the current literature, including the learning curve, generating confusing and subjective results. This study aims to create a scoring system to calculate the learning curve of LC based on hepatobiliopancreatic (HPB) experts' opinions during an educational course.
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- The study focuses on developing an AI system that automatically recognizes key anatomical landmarks during Trans Abdominal Pre Peritoneal (TAPP) hernia repair surgeries, enhancing dissection quality assessment.
- A deep neural network was trained on 130 surgical videos to identify critical structures like the pubic symphysis and iliac vein, with performance evaluated on a separate set of 30 videos.
- Results showcased a mean accuracy of 77.1% in video evaluations and significant agreement among surgeons on the landmark annotations, indicating the AI system's effectiveness and reliability.