Systematic Review of AI in Medical Education: Models and Frameworks, 2000-2025

A systematic narrative review synthesizing the theoretical development of artificial intelligence in medical training. The review, authored by Khalid A. Bin Abdulrahman and published in April 2026, analyzed 48 studies from a literature search covering January 2000 to March 2025. It focuses on educational models, frameworks, learning outcomes, and stakeholder considerations.

Use Cases

• Identify major AI application domains in medical education based on the five domains (Intelligent Tutoring Systems, Simulation-Based Medical Education, Adaptive Learning, Generative AI, Explainable AI) described in the review.
• Analyze stakeholder considerations and ethical challenges for responsible AI implementation based on the discussion of pedagogical, ethical, and practical challenges.
• Trace the theoretical evolution of AI in medical education based on the described progression from rule-based to data-driven machine learning models.
• Review synthesized guidance for educators and policymakers based on the conclusions of the systematic review.

Strengths

• Clear temporal scope covering literature from January 2000 to March 2025.
• Systematic methodology involving a search of four databases (PubMed, Scopus, Web of Science, Google Scholar) and qualitative synthesis of 48 included studies.
• Published under a permissive CC-BY-4.0 license, allowing for reuse and adaptation.

Limitations

• The dataset is a single 178.4 KB PDF document, representing a limited textual scope rather than a large-scale data collection.
• Row count and column-level documentation are absent; the content is a narrative review, not structured data.
• The review notes methodological heterogeneity in the included studies, which prevented a statistical meta-analysis.

Provenance

Source

figshare

Collection Method

Systematic narrative review of literature from PubMed, Scopus, Web of Science, and Google Scholar.

Time Range

January 2000 to March 2025

Freshness

Last updated 2026-04-20 05:19:38.

Geography

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