Latest AI and machine learning research in medical education for healthcare professionals.
Molecular simulations are invaluable for analysing molecular systems, but existing post-processing tools are often limited by a lack of customization, interactivity, and efficiency with large datasets. To address this, we developed CRISP (Comprehensive Repository for Insightful Simulation Post-Processing), an open-source Python toolkit designed to enhance workflows within the Atomic Simulation Env...
This study introduces an artificial intelligence-human-in-the-loop (AI-HITL) process to create an instrument for evaluating the quality of learning outcomes (LOs) in a veterinary curriculum. Although clear LOs are essential for competence-based education, their quality often varies, and traditional manual review is inconsistent and time-consuming. We used a large language model (ChatGPT-4o) to gen...
The disappearance of spontaneous student-generated drawings in examinations induced us to start developing anatomical drawing tasks that would be usef...
This study adopts a quantitative research design employs the UNESCO Teacher AI Competency Framework to assess and validate the artificial intelligence...
Accurate, continuous monitoring of psychophysiological states is central to understanding stress and autonomic dysfunction across diverse medical cont...
BACKGROUND: This systematic review and meta-analysis aimed to evaluate and quantitatively synthesize the effectiveness of artificial intelligence (AI)...
BACKGROUND: The global shortage of psychiatrists limits learners' exposure to authentic patient encounters. Simulation can support scalable deliberate...
Artificial intelligence (AI) is rapidly reshaping healthcare and the competencies expected of graduating medical students, yet AI curricula and compet...
BACKGROUND: Paediatric content in undergraduate nursing education is typically delivered through lectures, simulation, and clinical placements. Constr...
OBJECTIVE: Musculoskeletal dynamics influence the progression and rehabilitation of movement-related conditions. However, estimating whole-body dynami...
OBJECTIVE: This study aimed to develop prediction models for symptoms of poor mental health among Lebanese adults and adult Syrian refugees or migrant...
Evidential test data of genotyping softwares must clearly carry the characteristics of real-life evidential trace profiles. Ensuring that simulated da...
AIMS: To investigate the usage, implications, and perceptions of ChatGPT among dental students and understand how students incorporate ChatGPT into th...
OBJECTIVE: To assess psychiatry faculty knowledge, use, and perceptions of artificial intelligence (AI) in undergraduate medical education (UME) and g...
OBJECTIVE: This study compared the efficacy of Popular Science (PS) and Research-Based (RS) curriculum extensions in a Histology and Embryology course...
BACKGROUND: Meta-therapy (MT) is a powerful dialogue-based element of voice therapy that scaffolds patients' cognitive models of treatment. MT dialogu...
Among additive manufacturing (AM), 3D inkjet technology, materials extrusion (ME), and digital light processing (DLP), which are from dot and line to ...
BACKGROUND: Agentic artificial intelligence (AI) systems employing multi-model architectures with iterative reasoning may surpass standard single-mode...
Supervised machine learning is a popular tool for predictor selection in large data sets. The choice of method is currently either based on theory, su...
BACKGROUND: Generative artificial intelligence (GenAI) is enhancing virtual patient simulations in health care education by enabling dynamic, adaptive...