AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

General Surgery

Showing 61 to 70 of 97 articles

Clear Filters

Mining patient-specific and contextual data with machine learning technologies to predict cancellation of children's surgery.

International journal of medical informatics
BACKGROUND: Last-minute surgery cancellation represents a major wastage of resources and can cause significant inconvenience to patients. Our objectives in this study were: 1) To develop predictive models of last-minute surgery cancellation, utilizin...

Segmenting and classifying activities in robot-assisted surgery with recurrent neural networks.

International journal of computer assisted radiology and surgery
PURPOSE: Automatically segmenting and classifying surgical activities is an important prerequisite to providing automated, targeted assessment and feedback during surgical training. Prior work has focused almost exclusively on recognizing gestures, o...

Toward versatile cooperative surgical robotics: a review and future challenges.

International journal of computer assisted radiology and surgery
PURPOSE: Surgical robotics has developed throughout the past 30 years resulting in more than 5000 different approaches proposed for various surgical disciplines supporting different surgical task sequences and differing ways of human-machine cooperat...

Machine learning for identification of surgeries with high risks of cancellation.

Health informatics journal
Surgery cancellations waste scarce operative resources and hinder patients' access to operative services. In this study, the Wilcoxon and chi-square tests were used for predictor selection, and three machine learning models - random forest, support v...

Surgical trainee impact on bariatric surgery safety.

Surgical endoscopy
BACKGROUND: Roux-en-Y-gastric bypass (RYGB) and sleeve gastrectomy (SG) are commonly performed bariatric procedures that are associated with a significant learning curve. The effect of surgeon experience on perioperative outcomes and safety is establ...

Effective deep learning training for single-image super-resolution in endomicroscopy exploiting video-registration-based reconstruction.

International journal of computer assisted radiology and surgery
PURPOSE: Probe-based confocal laser endomicroscopy (pCLE) is a recent imaging modality that allows performing in vivo optical biopsies. The design of pCLE hardware, and its reliance on an optical fibre bundle, fundamentally limits the image quality w...

Investigating the Effect of Simulator Functional Fidelity and Personalized Feedback on Central Venous Catheterization Training.

Journal of surgical education
OBJECTIVE: To compare the effect of simulator functional fidelity (manikin vs a Dynamic Haptic Robotic Trainer [DHRT]) and personalized feedback on surgical resident self-efficacy and self-ratings of performance during ultrasound-guided internal jugu...

MILS in a general surgery unit: learning curve, indications, and limitations.

Updates in surgery
Minimally invasive liver surgery (MILS) is going to be a method with a wide diffusion even in general surgery units. Organization, learning curve effect, and the environment are crucial issues to evaluate before starting a program of minimally invasi...

Robotic general surgery: current practice, evidence, and perspective.

Langenbeck's archives of surgery
BACKGROUND: Robotic technology commenced to be adopted for the field of general surgery in the 1990s. Since then, the da Vinci surgical system (Intuitive Surgical Inc, Sunnyvale, CA, USA) has remained by far the most commonly used system in this doma...