ArticleMedicine2026
Mapping the research landscape of virtual reality and artificial intelligence in medical education evaluation: A bibliometric analysis.
Article in Medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEvaluation of medical education is essential for ensuring the quality of health professional training. However, conventional evaluation approaches often lack objectivity, scalability, and longitudinal assessment capacity. Virtual reality (VR) and artificial intelligence (AI) are increasingly integrated into medical education, yet their application in educational evaluation has not been systematically characterized.
objectiveTo examine research trends, thematic evolution, and emerging directions in VR- and AI-enabled medical education evaluation, a bibliometric analysis was conducted.
methodsPublications indexed in the Web of Science Core Collection between January 1, 2015, and December 31, 2025, were retrieved using predefined search terms related to VR, AI, medical education, and evaluation. Eligible English-language articles and reviews were analyzed using CiteSpace (version 6.4.R2). Annual publication and citation trends, country collaboration patterns, and cited journals were assessed. Research themes and frontiers were examined through keyword co-occurrence, clustering, burst detection, and timeline analyses.
resultsA total of 695 publications were included. Annual publications and citations increased steadily, with accelerated growth after 2020. The United States, Germany, China, England, and Canada produced the highest number of publications, whereas Belgium, Egypt, Sweden, Singapore, and Switzerland demonstrated high collaboration centrality. Influential cited journals were concentrated in medical education and simulation-based training domains. Keyword analyses identified major themes including surgical education, VR simulation, clinical reasoning, decision support, and residency and undergraduate education. Burst and timeline analyses indicated a progression from early simulation-based skill validation toward learner-centered performance evaluation and, more recently, quality-oriented and curriculum-level assessment.
conclusionsResearch on VR- and AI-enabled medical education evaluation has expanded rapidly and evolved from technical skill assessment toward comprehensive, competency-oriented, and quality-focused evaluation. These findings highlight the growing role of emerging technologies in shaping future global medical education evaluation frameworks.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.