Latest AI and machine learning research in medical education for healthcare professionals.
Background Effective communication skills are essential for quality medical practice and patient care, yet providing sufficient practice opportunities remains challenging in medical education. Traditional approaches using standardized patients (SPs) face limitations, including high costs and logistical constraints. This study investigates the potential of conversational artificial intelligence (AI...
Healthcare simulation scenario design remains a resource-intensive process, demanding significant time and expertise from educators. This article presents an innovative AI-driven agentic workflow for healthcare simulation scenario development, bridging technical capability with pedagogical effectiveness. The system evolved from an initial ChatGPT-based prototype to a sophisticated platform impleme...
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 ...
BACKGROUND: Standardized patients (SPs) prepare medical students for difficult conversations with patients. Despite their value, SP-based simulation t...
Hierarchical mixed-effects models with three trees-3Trees models-are a new advanced statistical learning approach in mixed-effect modeling. These meth...
Identification of groundwater pollution sources (IGPSs) is a prerequisite for pollution remediation and pollution risk prediction. Data assimilation a...
Fine-grained classification of whole slide images (WSIs) is essential in precision oncology, enabling precise cancer diagnosis and personalized treatm...
Dexterous manipulation remains an aspirational goal for autonomous robotic systems, particularly when learning to lift and rotate objects against grav...
BACKGROUND: Artificial intelligence (AI) integration in nursing simulation education is growing, yet understanding its implementation across simulatio...
IMPORTANCE: Large language models (LLMs) are being implemented in health care. Enhanced accuracy and methods to maintain accuracy over time are needed...
The integration of artificial intelligence (AI) into education is transforming learning across various domains, including dentistry. Endodontic educat...
The manufacturing industry heavily relies on welding processes to join materials, forming integral components across various sectors. Many aspects wil...