Latest AI and machine learning research in medical education for healthcare professionals.
This study develops an intelligent e-commerce talent demand prediction system built on a hybrid Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN) architecture, designed to support vocational college program optimization under China's Double First-Class Initiative. The hybrid model pairs LSTM networks for temporal sequence modeling with CNN components for spatial feature extracti...
BACKGROUND: Operating room (OR) inefficiency persists despite decades of process improvement, largely due to stochastic case durations, emergency disruptions, and resource coupling across pre-, intra-, and postoperative steps. While artificial intelligence (AI) methods are increasingly proposed for OR scheduling and allocation, most evaluations are single-method, single-site, or non-comparative, l...
The acronym "SP" is widely used in simulation-based education, yet its meaning varies across contexts, referring at different times to standardized pa...
This pilot study explored how adult day centers can serve as transformative clinical learning environments for nursing students to learn dementia care...
Health care professionals face an urgent need for AI literacy as artificial intelligence technologies rapidly transform clinical practice, yet nursing...
BACKGROUND: Artificial intelligence-enabled ambient speech recognition technology is an emerging innovation poised to transform how nurses care for an...
Deep Reinforcement Learning (DRL) methods have shown remarkable success in many applications, yet their high energy consumption limits their practicab...
The incorporation of AI-powered applications into music education is becoming increasingly important, as these tools can extend practice support beyon...
BACKGROUND: This article explores how preclinical students in a UK medical school utilise ChatGPT during their case-based learning (CBL) curriculum. M...
BACKGROUND: Positioning accuracy in radiotherapy is critical for treatment outcomes, especially in head tumor radiotherapy, where the target area is s...
Purpose Artificial intelligence (AI) is increasingly used in health professions education, yet little is known about dental hygiene students' knowledg...
The high nominal accuracy achieved by deep learning models in predicting malignant skin lesions is frequently undermined by their susceptibility to op...
Recent advancements in artificial intelligence have led to increased interest in predictive modeling across various domains, including medicine. Altho...
BACKGROUND: Advances in artificial intelligence have brought renewed attention to tools that can work with the large amount of written information gen...
Video laryngoscopy has become an integral part of today's airway management. Despite its advantages, loss of depth perception and increased cognitive ...
There is simultaneously a global shortage of mental health professionals and a rising demand for mental health services. Nurses provide the largest sh...
BACKGROUND: Generative AI (GenAI) has increasingly been used in ways to support health professions education but the utility of it to support research...
In 2005, Weill Cornell Medicine revised the Hippocratic Oath. Since then, this revised oath has been administered to graduating medical students and b...
The integration of artificial intelligence (AI) into curriculum and instruction provides a new challenge facing pharmacy educators. This article explo...
PURPOSE: Artificial intelligence (AI) in medical education is rapidly evolving. The nascent literature about the use of AI in clerkships is sparse. In...