AIMC Topic: Education, Medical

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Twelve Practical Tips for Integrating AI Into Medical Education: Tutorial to Support Educators Across Teaching, Research, Administration, and Ethical Domains.

JMIR medical education
Artificial intelligence (AI) is rapidly reshaping medical education, offering new opportunities to personalize learning, enhance research, and streamline administration. The aim of this study is to provide 12 practical, evidence-informed tips by draw...

What Are the Opportunities and Challenges of Using AI in Medical Education in Vietnam?

JMIR medical education
Artificial intelligence (AI) has the potential to transform medical training through adaptive learning, immersive simulations, automated assessments, and data-driven insights, offering solutions to persistent issues such as high student-to-faculty ra...

Assessing the quality and educational applicability of AI-generated anterior segment images in ophthalmology.

Scientific reports
Text-to-image (T2I) artificial intelligence models are being increasingly explored in medical education, yet their utility in ophthalmology remains unclear. Slit-lamp anterior segment photography, as a cornerstone of ophthalmic training, provides an ...

AI-Enhanced Social Robotic Versus Computer-Based Virtual Patients for Clinical Reasoning Training in Medical Education: Observational Crossover Cohort Study.

Journal of medical Internet research
BACKGROUND: Virtual patient (VP) simulations can be used to practice clinical reasoning (CR) in controlled learning environments. Traditional computer-based VP platforms often lack the authenticity and interactivity required for effective CR training...

A research roadmap for AI opportunities in student assessment for medical education.

BMC medical education
The integration of Artificial Intelligence (AI) in medical education is rapidly transforming assessment practices, offering unprecedented opportunities to enhance student evaluation, feedback, and learning pathways. However, despite the potential, a ...

The pitfalls of multiple-choice questions in generative AI and medical education.

Scientific reports
The performance of Large Language Models (LLMs) on multiple-choice question (MCQ) benchmarks is frequently cited as proof of their medical capabilities. We hypothesized that LLM performance on medical MCQs may in part be illusory and driven by factor...

Reimagining healthcare education through nurturing AI-driven innovation.

BMC medical education
PURPOSE: This article explores the transformative role of artificial intelligence (AI) in healthcare medical education, highlighting the urgent need to integrate AI into medical curricula. It examines the current gaps in AI literacy among healthcare ...

Rare disease education in medical schools: patient-centered and innovative strategies.

Orphanet journal of rare diseases
PURPOSE: Globally, approximately 300 million people live with a rare disease, while in the United States, nearly 30 million, or 1 in 10 Americans, have a rare disease or disorder (RD) (The Lancet Global Health. Lancet Glob Health 2024. https://doi.or...

Teaching Clinical Reasoning in Health Care Professions Learners Using AI-Generated Script Concordance Tests: Mixed Methods Formative Evaluation.

JMIR formative research
BACKGROUND: The integration of artificial intelligence (AI) in medical education is evolving, offering new tools to enhance teaching and assessment. Among these, script concordance tests (SCTs) are well-suited to evaluate clinical reasoning in contex...

How AI Is Transforming Medical Education: Bibliometric Analysis.

JMIR medical education
BACKGROUND: Artificial intelligence (AI) is increasingly being integrated into medical education. As AI technologies continue to evolve, they are expected to enable more sophisticated student tutoring, performance evaluation, and reforms of curricula...