BMC Medical Education welcomed submissions to a Collection entitled “Artificial intelligence in medical and professional health education.” This Collection aims to explore the dynamic intersection between artificial intelligence and medical education to promote the efficacy of international healthcare practitioners and the care they can provide to their patients.
Artificial intelligence is rapidly transforming all areas of healthcare, and medical education is no exception. This Collection seeks to examine the ways in which AI is changing the landscape of medical education, from its role in training medical students to its impact on continuing education and professional development for healthcare providers.
Interdisciplinary research on this topic has the potential to significantly improve patient outcomes and overall quality of care. In medical training and educational environments, AI-powered virtual patient simulations have been shown to improve the clinical decision-making abilities of medical students and contribute to improved patient safety and outcomes. Continued research in this area could lead to even more innovative applications of AI in medical education, such as personalized learning algorithms that adapt to the unique needs of individual learners. By improving the quality of medical education in classrooms and beyond, this research has the potential to revolutionize medical education and lead to improved quality of care for patients worldwide.
We invited the submission of innovative new research that contributes to that goal. The scope of this Collection includes, but is not limited to, the following topics:
• Incorporating artificial intelligence into medical education curriculums
• AI-powered simulation-based training, personalized learning, student assessments, and evaluation methods
• The integration of AI into continuing education and professional development for healthcare providers, such as AI-powered decision support systems and virtual patient simulations
• Ethical and social implications of AI in medical education, including issues of bias, privacy, and patient autonomy
• Innovative applications of AI in medical education
• Theories behind the use of AI in medical education and training
We welcomed contributions from diverse perspectives, including healthcare professionals, medical educators, social scientists, and computer scientists. Further, we hope to include occupational research on dentistry, pharmacy, nursing, physiotherapy, occupational therapy, speech pathology, psychology, midwifery, oral therapy, paramedicine, and optometry. Our goal is to create a vibrant and interdisciplinary Collection that highlights the latest research and developments in AI and medical education.
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