Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
AI in medical education
2
Zitationen
1
Autoren
2024
Jahr
Abstract
Artificial intelligence (AI) is revolutionizing various fields, and its impact on healthcare education and clinical practice is expected to be profound. This chapter explores the key opportunities and considerations for successfully implementing AI in healthcare education. Six key guiding principles are discussed: adaptive systems approach, ethical considerations, evidence-based learning, human-centered design, an integrative approach, and change leadership. The chapter discusses the importance of learning about AI, including the development of core AI-related competencies and skills. It also discusses learning with AI, utilizing AI-powered tools to support healthcare education that enable knowledge on demand, AI-powered simulations, and adaptive learning and assessment. By following these principles and incorporating AI into medical education , healthcare professionals can effectively prepare for the AI-focused future in healthcare and improve patient care.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.200 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.051 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.416 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.410 Zit.