The role of artificial intelligence in medical learning improvement: A systematic review
Code: G-1419
Authors: Hajar Karimtabar ℗, Saeid Hosseinoghli *, Negin Vaez
Schedule: Not Scheduled!
Tag: Intelligent Virtual Assistant
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Abstract:
Abstract
Introduction: nowadays by growing health care, its need to medical education reform will increase too. as the artificial intelligence (AI) development and its applications in many different subjects, usage of AI in medical education has attracted more attention from researchers and medical educators. we decided to systematically review the past studies to evaluate the application of AI in medical learning improvement among students. Methods: Electronic databases of PubMed, Scopus and Web of Science were searched from January 2010 to October 2024 to identify peer-reviewed articles that investigated AI applications in medical education, so that they are not limited to adaptive learning systems, virtual simulations, and intelligent tutoring systems. Data extraction was performed by two reviewers independently, and findings qualitatively were synthesized by the third person. Results: Of 15124 articles initially identified, 30 studies met the inclusion criteria, which included AI applications such as personalized learning platforms, predictive analytics for student performance, and automated feedback mechanisms. The result shows the AI-enhanced learning had significant improvement in student engagement so that improved knowledge retention (average increase of 30%) and clinical reasoning skills. It is worth to noting that there were some challenges that could affect our result such as data privacy concerns, integration with existing curricula, and varying levels of technological proficiency among educators. Conclusion: the offer of tailored educational experiences and enhancing assessment methods will improve medical learning. We suggest exploring AI long-term impacts on clinical competencies and investigating practices for AI integration into medical curricula as future studies.
Keywords
Artificial Intelligence, Medical Education, Learning Improvement
