Latest AI and machine learning research in medical education for healthcare professionals.
This special article is the fourth in an annual series for the Journal of Cardiothoracic and Vascular Anesthesia that highlights significant literature from the world of graduate medical education that was published over the past year. Some of the major themes that will be addressed in this review include the use of artificial intelligence by both applicants and training programs, the deployment o...
INTRODUCTION: A growing area is the use of ChatGPT in simulation-based learning, a widely recognized methodology in medical education. This study aimed to evaluate ChatGPT's ability to generate realistic simulation scenarios to assist faculty as a significant challenge in medical education.
As Otago Medical School marks its 150th anniversary, this paper reflects on what it means to train doctors for both today and the decades ahead. It tr...
The rising cancer incidence has increased demand for radiation oncologists, surpassing current staffing expansion estimates. Enhancing radiation oncol...
: Hospital readmissions are a key quality metric impacting both patient outcomes and healthcare costs. Traditional logistic regression models, includi...
Due to their excellent specific strength and lightweight characteristics, Al-Cu-Li alloys are widely used in aerospace applications. The newly develop...
Faculty in dental and health professions education face growing workloads, leading to stress, burnout, and attrition. To address these challenges, Lar...
Study DesignA comparative analysis of AI-generated vs human-authored personal statements for spine surgery fellowship applications.ObjectiveTo assess ...
PROBLEM: Despite the rapidly expanding role of artificial intelligence (AI) and machine learning (ML) in health care, a significant knowledge gap rema...
Background Effective communication skills are essential for quality medical practice and patient care, yet providing sufficient practice opportunities...
Healthcare simulation scenario design remains a resource-intensive process, demanding significant time and expertise from educators. This article pres...
Carbon nanotubes (CNTs), as a promising nanomaterial with broad applications across various fields, are continuously attracting significant research a...
Generative Artificial Intelligence (GenAI) is increasingly being used in medical education, including the creation of content for clinical virtual pat...
Aiming to solve the problems of low precision and poor efficiency caused by relying on manual experience during the manual polishing of blades, a mult...
In this study, we present a hybrid Physics-Assisted Machine Learning (PAML) model that integrates Deep Learning (DL) techniques with the classical Dis...
BACKGROUND: Simulation-based medical education (SBME) is a critical training tool in healthcare, shaping learners' skills, professional identities, an...
Healthcare systems are increasingly integrating artificial intelligence and machine learning (AI/ML) tools into patient care, potentially influencing ...
BACKGROUND: As health care moves to a more digital environment, there is a growing need to train future family doctors on the clinical uses of artific...
INTRODUCTION: The application of artificial intelligence (AI) in the assessment of procedural skills on a simulation platform using the global rating ...