AIMC Topic: Clinical Competence

Clear Filters Showing 471 to 480 of 691 articles

The Extended Supervised Learning Event (ESLE): Assessing Nontechnical Skills in Emergency Medicine Trainees in the Workplace.

Annals of emergency medicine
STUDY OBJECTIVE: The contribution of emergency medicine clinicians' nontechnical skills in providing safe, high-quality care in the emergency department (ED) is well known. In 2015, the UK Royal College of Emergency Medicine introduced explicit valid...

Artificial Intelligence in Aortic Surgery: The Rise of the Machine.

Seminars in thoracic and cardiovascular surgery
The first concept of Artificial Intelligence (AI) came into attention during 1920s and currently it is rapidly being integrated in our daily clinical practice. The use of AI has evolved from basic image-based analysis into complex decisions related t...

Novel evaluation of surgical activity recognition models using task-based efficiency metrics.

International journal of computer assisted radiology and surgery
PURPOSE: Surgical task-based metrics (rather than entire procedure metrics) can be used to improve surgeon training and, ultimately, patient care through focused training interventions. Machine learning models to automatically recognize individual ta...

Gastroenterologist-Level Identification of Small-Bowel Diseases and Normal Variants by Capsule Endoscopy Using a Deep-Learning Model.

Gastroenterology
BACKGROUND & AIMS: Capsule endoscopy has revolutionized investigation of the small bowel. However, this technique produces a video that is 8-10 hours long, so analysis is time consuming for gastroenterologists. Deep convolutional neural networks (CNN...

Performance of a Deep-Learning Neural Network to Detect Intracranial Aneurysms from 3D TOF-MRA Compared to Human Readers.

Clinical neuroradiology
PURPOSE: To study the clinical potential of a deep learning neural network (convolutional neural networks [CNN]) as a supportive tool for detection of intracranial aneurysms from 3D time-of-flight magnetic resonance angiography (TOF-MRA) by comparing...

Handheld laparoscopic robotized instrument: progress or challenge?

Surgical endoscopy
BACKGROUND: Handheld laparoscopic robotized instruments have been developed to combine the advantages of a robotic operation system and conventional laparoscopic instruments. Direct objective standards are needed to quantify surgeons' skill level and...

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 ...

Machine learning classifiers can predict Gleason pattern 4 prostate cancer with greater accuracy than experienced radiologists.

European radiology
OBJECTIVE: The purpose of this study was: To test whether machine learning classifiers for transition zone (TZ) and peripheral zone (PZ) can correctly classify prostate tumors into those with/without a Gleason 4 component, and to compare the performa...

Concepts in U.S. Food and Drug Administration Regulation of Artificial Intelligence for Medical Imaging.

AJR. American journal of roentgenology
Although extensive attention has been focused on the enormous potential of artificial intelligence (AI) technology, a major question remains: how should this fundamentally new technology be regulated? The purpose of this article is to provide an ove...