⚡ Quick Summary

This scoping review explores the integration of artificial intelligence (AI) in undergraduate medical education (UME), highlighting the need for a standardized curriculum that emphasizes ethical training and digital competence. The findings reveal significant global discrepancies in AI curriculum development and implementation.

🔍 Key Details

• 📊 Studies Reviewed: 34 studies from diverse regions
• 🧩 Focus Areas: Curriculum development, student competency, institutional barriers
• ⚙️ Methodology: Thematic analysis of articles published from 2019 onwards
• 🌍 Languages: English and Spanish publications only

🔑 Key Takeaways

• 📚 AI integration in UME is essential for preparing future physicians.
• ⚖️ Ethical training is a critical component of AI education.
• 🤝 Collaborative learning enhances student competency in using AI technologies.
• 💻 Digital competence is necessary for effective AI application in clinical settings.
• 🌐 Global discrepancies exist in AI curriculum frameworks across regions.
• 🔄 Transversal skills should be prioritized over treating AI as a standalone subject.
• 📈 Further research is needed to develop culturally relevant AI frameworks.

📚 Background

The integration of artificial intelligence in healthcare has significantly transformed clinical practices and medical education. However, there remains a notable gap in adequately preparing future physicians to utilize these technologies effectively and ethically. As AI continues to evolve, it is crucial to ensure that medical education keeps pace with these advancements.

🗒️ Study

This scoping review aimed to map the integration of AI in undergraduate medical education by analyzing 34 studies published since 2019. The researchers focused on curriculum development, enhancement of student competencies, and the institutional barriers that hinder the adoption of AI in medical training.

📈 Results

The review revealed a lack of standardized AI curriculum frameworks across various institutions. Key elements identified as essential for effective AI education included ethical training, collaborative learning, and digital competence. The emphasis on transversal skills indicates a need for AI to be embedded within interdisciplinary, patient-centered frameworks rather than treated as a separate subject.

🌍 Impact and Implications

The findings of this review underscore the importance of developing a standardized, adaptable AI curriculum in undergraduate medical education. By prioritizing ethical awareness and digital competence, institutions can better prepare future healthcare professionals to integrate AI technologies into their practice. This balanced approach fosters a more comprehensive understanding of AI as a tool that enhances patient care rather than a standalone entity.

🔮 Conclusion

This scoping review highlights the critical need for a cohesive and standardized approach to AI integration in medical education. By embedding AI within a framework that emphasizes ethical training and digital skills, we can ensure that future physicians are well-equipped to navigate the complexities of technology in healthcare. Continued research and collaboration are essential to develop frameworks that align with diverse cultural and educational needs.

💬 Your comments

What are your thoughts on the integration of AI in medical education? How do you think we can better prepare future physicians for this technological shift? 💬 Share your insights in the comments below or connect with us on social media:

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