Latest AI and machine learning research in medical education for healthcare professionals.
In the rapidly advancing landscape of surgical education, the traditional apprenticeship model is being increasingly complemented by individualized learning, competency-based assessment, and data-driven feedback. Work-hour restrictions, administrative burdens, and limited operative exposure have intensified the need for innovative solutions to supplement faculty-led training. Artificial intelligen...
RATIONALE AND OBJECTIVES: Large language models (LLMs) are increasingly investigated in radiology education. This study evaluated the performance of several advanced LLMs on radiology residency in-training examination questions, with a focus on whether recently released versions show improved accuracy compared with earlier models. MATERIALS AND METHODS: We analyzed 282 multiple-choice questions (1...
Mix-up is a key technique for consistency regularization-based semi-supervised learning methods, blending two or more images to generate strong-pertur...
INTRODUCTION AND OBJECTIVES: An AI model that performs well during training does not guarantee similar performance in clinical practice and should be ...
BACKGROUND: Intensive Care Unit (ICU) nursing is demanding, requiring advanced clinical decision-making and emergency management skills. Simulation-ba...
The intrinsic dynamics and event-driven nature of spiking neural networks (SNNs) make them excel in processing temporal information by naturally utili...
AIMS: The study focused on nurses' familiarity with, beliefs about, and attitudes towards artificial intelligence, aiming to identify configurations o...
Transcranial ultrasound imaging plays an important role in the diagnosis of brain diseases and the monitoring of brain function. However, the quality ...
The shortage of clinical training sites and preceptors has become a major barrier in the development of health workforce across North America. Innovat...
PURPOSE: To develop a 3D multiple overlapping-echo detachment (3D-MOLED) imaging technique, along with data generation and reconstruction strategies, ...
CLINICAL RELEVANCE: Communication between eye care practitioners is essential to optimise health care. Traditionally, actors have been used prior to r...
This study explored nurses' perspectives on the adoption and utilization of artificial intelligence (AI) in clinical practice within a large universit...
INTRODUCTION: Artificial intelligence tools show promise in supplementing traditional physician assistant education, particularly in developing clinic...
To gain molecular and mechanistic insights into initiation of the RAS-RAF signaling cascade, we developed and used a combination of multiscale simulat...
This article applies the multicultural orientation framework (D. E. Davis et al., 2018) to enhance religious/spiritual competencies. The skills gap in...
BACKGROUND: Microsurgery is associated with a steep learning curve that requires extensive training through supervised surgeries, cadaver practice, an...
Delivering feedback is a critical skill that remains widely underdeveloped among medical educators. Faculty development in this area has traditionally...
Prospective university students are highly susceptible to mental health issues such as depression and anxiety. This study investigates the prevalence ...
Large language models (LLMs) have shown promising capabilities across medical disciplines, yet their performance in basic medical sciences remains inc...