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Updated: Feb 19, 2026

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

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Artificial Intelligence in Medical Education: Transformative Potential, Current Applications, and Future

Juan S Izquierdo-Condoy1, Marlon Arias-Intriago1, Laura Montero Corrales2

  • 1One Health Research Group, Universidad de Las Américas, Via Nayon S/N, Quito, 170124, Ecuador, +593 995760693.

JMIR Medical Education
|February 17, 2026
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) enhances medical education through adaptive learning and AI-assisted tools. Responsible integration requires addressing ethical concerns and ensuring equitable access for improved learning outcomes.

Keywords:
adaptive learning systemsartificial intelligencefuture implicationsmachine learningmedical education

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Area of Science:

  • Medical Education Technology
  • Artificial Intelligence in Healthcare
  • Digital Learning Strategies

Background:

  • Artificial intelligence (AI) is transforming medical education with adaptive learning, AI-assisted assessment, and scalable tools.
  • Technologies like natural language processing, machine learning, and generative large language models offer novel teaching and learning support.
  • Integration of AI presents significant ethical, pedagogical, and infrastructural challenges.

Purpose of the Study:

  • To examine current AI applications, benefits, and challenges in medical education.
  • To propose strategies for responsible and effective AI integration in medical training.
  • To provide a framework for evaluating AI's impact on medical education.

Main Methods:

  • Review of AI applications including chatbots, virtual patients, and intelligent tutoring systems.
  • Analysis of AI tools for assessment, such as automated grading and predictive analytics.
  • Examination of AI-assisted content creation tools.

Main Results:

  • AI tools enhance personalized, immersive learning and streamline content creation.
  • AI offers efficient evaluation methods through automated grading and predictive analytics.
  • Concerns include data privacy, algorithmic bias, unequal access, and potential impact on critical thinking.

Conclusions:

  • AI presents substantial opportunities to revolutionize medical education.
  • Ethical, equitable, and pedagogically sound integration is crucial for AI adoption.
  • Frameworks like FACETS, institutional governance, and collaboration are key to successful AI implementation.