AIMC Topic: General Surgery

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Expectations versus reality: trainee participation on the robotic console in academic surgery.

Surgical endoscopy
INTRODUCTION: Trainees underestimate the amount of operative autonomy they receive, whereas faculty overestimate; this has not been studied in robotics. We aimed to assess the perceptions and expectations of our general surgery trainees and faculty o...

Mechanizing medicine - Tomorrows history started yesterday.

American journal of surgery
History is by nature a retrospective subject, there usually being an interval between any event, a review or impact of the subject being considered. This NPSA Historian's paper, takes a long and quick historical view of influences that fostered chang...

Towards near real-time assessment of surgical skills: A comparison of feature extraction techniques.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Surgical skill assessment aims to objectively evaluate and provide constructive feedback for trainee surgeons. Conventional methods require direct observation with assessment from surgical experts which are both unscalable a...

A machine learning approach to predict surgical learning curves.

Surgery
BACKGROUND: Contemporary surgical training programs rely on the repetition of selected surgical motor tasks. Such methodology is inherently open ended with no control on the time taken to attain a set level of proficiency, given the trainees' intrins...

The digital surgeon: How big data, automation, and artificial intelligence will change surgical practice.

Journal of pediatric surgery
Exponential growth in computing power, data storage, and sensing technology has led to a world in which we can both capture and analyze incredible amounts of data. The evolution of machine learning has further advanced the ability of computers to dev...

Accurate and interpretable evaluation of surgical skills from kinematic data using fully convolutional neural networks.

International journal of computer assisted radiology and surgery
PURPOSE: Manual feedback from senior surgeons observing less experienced trainees is a laborious task that is very expensive, time-consuming and prone to subjectivity. With the number of surgical procedures increasing annually, there is an unpreceden...

Artificial Intelligence in Medical Education: Best Practices Using Machine Learning to Assess Surgical Expertise in Virtual Reality Simulation.

Journal of surgical education
OBJECTIVE: Virtual reality simulators track all movements and forces of simulated instruments, generating enormous datasets which can be further analyzed with machine learning algorithms. These advancements may increase the understanding, assessment ...

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...