Latest AI and machine learning research in medical education for healthcare professionals.
OBJECTIVE: The rapid advancement of Large Language Models (LLMs) has generated interest in their application to medical education, particularly for high-stakes assessments like the USMLE. This study aims to evaluate the performance of DeepSeek-R1, a state-of-the-art LLM developed in China, compared to OpenAI models, to assess its feasibility for medical education and assessment. METHODS: The autho...
BACKGROUND: Artificial intelligence (AI) is increasingly integrated into public health and dentistry, with a range of applications. While these developments raise questions about efficiency and scalability, uncertainty remains regarding whether AI can substitute for Dental Public Health (DPH) expertise. This paper aims to distinguish between AI-amenable and fundamentally human DPH competencies. ME...
BACKGROUND: Computational prediction of drug-target interaction (DTI) is critical for drug discovery and precision medicine. Herein, we constructed a ...
Large language models (LLMs) can achieve passing scores in specialist-level examinations, yet their capacity to author high-stakes examination content...
In drug discovery, it is not sufficient for a lead compound to exhibit high binding affinity for the target protein alone. It is equally important to ...
BACKGROUND AND INTRODUCTION: Society 5.0 envisions a future where technology and humanity integrate to address societal concerns. In an era marked by ...
Artificial intelligence (AI) is increasingly transforming health care through improvements in diagnosis, predictive analytics, and workflow optimizati...
Vegetation restoration is widely regarded as a key measure for mitigating soil erosion in the middle reaches of the Yellow River. However, the regulat...
BACKGROUND: Large language models (LLMs) are increasingly used by patients for health information and preliminary medical advice. In patient-facing co...
PURPOSE OF REVIEW: This scoping review synthesizes contemporary evidence on the role of simulation, uro-technology and structured training curricula i...
BACKGROUND: Large language models (LLMs) are increasingly explored as tools for medical education. However, evidence remains limited regarding their p...
Debriefing is widely recognised as a central mechanism for learning within healthcare simulation, enabling learners to reflect on clinical actions, de...
Background. Simulation calibration is the process of configuring a simulation model's parameters to improve the agreement between the model output and...
INTRODUCTION: Traditional program evaluation in medical education often faces challenges with large data volumes and manual analysis, which can delay ...
BACKGROUND: Serious illness conversations (SICs) are an important part of medical care, yet trainees continue to express discomfort. Educational oppor...
Autonomous artificial intelligence (AI) systems for retinal image interpretation are being deployed in routine clinical practice, fundamentally alteri...
Simulation-based education has become widely embedded in health professional training and is increasingly positioned as a solution to clinical placeme...
Simulation-based education has evolved into a foundational component of nuclear medicine technologist training, driven by increasing procedural comple...
Simulation-based education has emerged as a strategic response to placement scarcity, workforce strain, and the increasing complexity of nuclear medic...
INTRODUCTION: Endoscopic Sleeve Gastroplasty (ESG) is an established minimally invasive bariatric intervention, while artificial intelligence (AI) has...