Systematic Review of AI in Medical Education, 2000-2025

A systematic narrative review synthesizing the theoretical development of artificial intelligence in medical training. The review analyzed 48 studies from a search of 1,288 records across PubMed, Scopus, Web of Science, and Google Scholar from January 2000 to March 2025. Author Khalid A. Bin Abdulrahman published the findings as a PDF document in April 2026 under a CC-BY-4.0 license.

Use Cases

• Identify major AI application domains in medical education based on the five domains described: Intelligent Tutoring Systems, Simulation-Based Medical Education, Adaptive Learning, Generative AI, and Explainable AI.
• Analyze stakeholder considerations and ethical challenges for AI implementation based on the discussion of learner deskilling, academic integrity, and algorithmic bias.
• Trace the theoretical progression of AI in education based on the review's synthesis of models, frameworks, and future directions.
• Guide curriculum development and policy based on the review's conclusions regarding responsible and effective AI integration.

Strengths

• The review is based on a systematic search of 1,288 records from four major academic databases.
• It includes a qualitative thematic synthesis of 48 studies that met specific inclusion criteria.
• The document covers a defined time range from January 2000 to March 2025.
• It is published under a permissive CC-BY-4.0 license, allowing for reuse and redistribution.

Limitations

• The dataset is a single 148.3 KB PDF document, representing a limited textual analysis rather than a primary data collection.
• Row count and column-level documentation are absent; the content structure must be inferred from the narrative.
• No statistical meta-analysis was conducted due to methodological heterogeneity among the included studies.

Provenance

Source

Khalid A. Bin Abdulrahman, via figshare.

Collection Method

Systematic narrative literature review.

Time Range

January 2000 – March 2025

Freshness

Last updated 2026-04-20 05:19:37

Geography

Global (studies sourced from international databases).