AI Medical Compendium Topic:
Clinical Competence

Clear Filters Showing 481 to 490 of 580 articles

Face, content, and construct validity of four, inanimate training exercises using the da Vinci ® Si surgical system configured with Single-Site ™ instrumentation.

Surgical endoscopy
BACKGROUND: Validated training exercises are essential tools for surgeons as they develop technical skills to use robot-assisted minimally invasive surgical systems. The purpose of this study was to show face, content, and construct validity of four,...

Variability of automated carotid intima-media thickness measurements by novice operators.

Clinical physiology and functional imaging
Carotid intima-media thickness (C-IMT) measurements provide a non-invasive assessment of subclinical atherosclerosis. The aim of the study was to assess the inter- and intra-observer variability of automated C-IMT measurements undertaken by two novic...

PhacoTrainer: Automatic Artificial Intelligence-Generated Performance Ratings for Cataract Surgery.

Translational vision science & technology
PURPOSE: To investigate whether cataract surgical skill performance metrics automatically generated by artificial intelligence (AI) models can differentiate between trainee and faculty surgeons and the correlation between AI metrics and expert-rated ...

The Role of AI in Reshaping Medical Education: Opportunities and Challenges.

The clinical teacher
Artificial intelligence (AI) is redefining medical education, bringing new dimensions of personalized learning, enhanced visualization and simulation-based clinical training to the forefront. Additionally, AI-powered simulations offer realistic, imme...

A glance into the future of artificial intelligence-enhanced scalable personalized training: A response to Kopelovich, Brian, et al. (2025) and Kopelovich, Slevin, et al. (2025).

Psychotherapy (Chicago, Ill.)
The two articles by Kopelovich, Brian, et al. (2025) and Kopelovich, Slevin, et al. (2025) mark a new era in psychotherapy research and practice. The articles detail the development and validation of one of the first conversational artificial intelli...

Can ChatGPT pass the Turkish Orthopedics and Traumatology Board Examination? Turkish orthopedic surgeons versus artificial intelligence.

Ulusal travma ve acil cerrahi dergisi = Turkish journal of trauma & emergency surgery : TJTES
BACKGROUND: Artificial intelligence has been shown to achieve successful outcomes in various orthopedic qualification examinations worldwide. This study aims to assess the performance of ChatGPT in the written section of the Turkish Orthopedics and T...

Association of machine-learning-rated supportive counseling skills with psychotherapy outcome.

Journal of consulting and clinical psychology
OBJECTIVE: This study applied a machine-learning-based skill assessment system to investigate the association between supportive counseling skills (empathy, open questions, and reflections) and treatment outcomes. We hypothesized that higher empathy ...

The Effect of Nursing Students' Artificial Intelligence Anxiety on Their Knowledge of Robotic Surgery: The Mediating Role of Individual Innovativeness.

Journal of evaluation in clinical practice
AIMS: This study aims of determine the mediating role of individual innovativeness in the effect of nursing students' artificial intelligence anxiety on their robotic surgery knowledge level.

Improving Nursing Students' Learning Outcomes in Neonatal Resuscitation: A Quasi-Experimental Study Comparing AI-Assisted Care Plan Learning With Traditional Instruction.

Journal of evaluation in clinical practice
AIM: The purpose of this study is to compare the efficacy of an artificial intelligence (AI)-based care plan learning strategy with standard training techniques in order to determine how it affects nursing students' learning results in newborn resusc...

The influence of a deep learning tool on the performance of oral and maxillofacial radiologists in the detection of apical radiolucencies.

Dento maxillo facial radiology
OBJECTIVES: This study aimed to assess the impact of a deep learning model on oral radiologists' ability to detect periapical radiolucencies on periapical radiographs. The secondary objective was to conduct a regression analysis to evaluate the effec...