Navigating the Digital Transformation of Healthcare Learning through Generative AI

The integration of generative artificial intelligence (GenAI) into healthcare professions education is a groundbreaking shift, poised to equip future healthcare providers with advanced tools, insights, and opportunities for medical education. This Research Topic explores how GenAI can fundamentally enhance educational protocols, practices, and learner outcomes in healthcare training, while also examining the challenges this emerging technology poses for educators and institutions. The efficacy of GenAI in revising educational methods and the potential hurdles, such as ethical considerations, acceptance among professionals, and curriculum integration are central focal points of this Research Topic.

This Research Topic will cover the multitude of diverse opportunities that GenAI can offer in medical educational settings, as well as critically analyze the barriers that might impede its potential impact. From improving personalized learning and feedback through advanced simulations and intelligent, responsive tutoring systems, to ensuring that future healthcare professionals are proficient in digital competencies necessary for handling AI tools and output, this collection will cover a broad range of considerations and perspectives relevant to GenAI in medical education.

To gather further insights on the opportunities and challenges of GenAI within healthcare professions education, we welcome articles addressing, but not limited to, the following themes:

  •  GenAI-driven educational technologies and customized learning experiences.
  •  Integration of GenAI into curricula to bolster clinical and diagnostic capabilities.
  •  GenAI's role in skill development and the assessment of healthcare learners.
  •  Potential GenAI misuse and undermining of learning and retention.
  •  Cross-disciplinary collaborations for effective GenAI implementation in education.
  •  Barriers to GenAI adoption in educational institutions and potential solutions.
  •  Attitudes of healthcare educators and/or learners towards GenAI and its impact on their role.
  •  Developing digital health competencies for GenAI applications in healthcare.
  •  Preparing learners for a GenAI-enabled healthcare professions workforce.
  •  Ethical, privacy, and security issues raised by the use of GenAI in educational settings.

This Research Topic seeks to stimulate discussion and foster innovation in medical educational practices, making sure these practices evolve to meet the digital demands of modern healthcare environments. We encourage submissions of all article types, but particularly original research, reviews, case studies, opinions, perspectives, and curriculum, instruction and pedagogy articles that provide insights into the utilization of GenAI in healthcare professions education.


Topic Editor Jeremy Richards and Topic Coordinator Elisabeth Schlegel are consultants for ScholarRx. All other Editors and Coordinators declare no conflicts of interest.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Clinical Trial
• Community Case Study
• Curriculum, Instruction, and Pedagogy
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Clinical Trial
• Community Case Study
• Curriculum, Instruction, and Pedagogy
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Policy Brief
• Review
• Study Protocol
• Systematic Review
• Technology and Code

Keywords: artificial intelligence, GenAI, large language models, LLMs, ChatGPT, healthcare professions education, medical education, personalized learning, precision medical education, digital health competency

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.