ReviewFrontiers in medicine2026
The digital transformation of medical education collaborative governance in the era of smart education: an innovative management restructuring of medical talent cultivation systems.
Review in Frontiers 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
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Smart education, supported by artificial intelligence (AI), big data, and virtual simulation, is reshaping medical education toward more flexible and collaborative models. However, persistent barriers-fragmented governance, limited data interoperability, and uneven resource distribution-continue to constrain effective collaboration between medical schools and teaching hospitals. This narrative review synthesizes recent developments in digital governance for medical education and proposes a four-layer framework comprising institutional foundations, cross-organizational mechanisms, platform-based technological support, and data-driven quality assurance. The review also highlights key implementation considerations, including interoperability standards for integrating educational and clinical data, staged technology adoption across different resource settings, and governance-oriented evaluation criteria for AI-enabled assessment (e.g., effectiveness, reliability, fairness, explainability, and human oversight). Finally, it discusses privacy, security, and algorithmic accountability challenges under different regulatory contexts. Overall, smart education may facilitate a transition toward more data-informed governance, while requiring context-sensitive implementation and robust ethical safeguards.
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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 OpenQuestion graph.