ReviewFrontiers in digital health2026
Artificial intelligence in undergraduate medical education clinical skills curricula: a scoping review of implementations since 2022.
Review in Frontiers in digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: To systematically identify and synthesize peer-reviewed literature describing implemented AI innovations within undergraduate medical education clinical skills curricula from January 2022 through January 2026. Method: The authors conducted a scoping review querying PubMed and Scopus, supplemented by SciSpace as an AI-assisted citation discovery tool. Eligible studies described utilizing AI to deliver the clinical skills curriculum in innovative ways (e.g., instruction in history-taking, communication, clinical reasoning, clinical documentation, OSCE/simulation assessment). We extracted data into standardized templates and thematically sorted to characterize how AI-assisted instruction was being implemented across educational objectives. Results: From 1,130 initial records, 39 studies met inclusion criteria. AI-assisted instruction clustered into eight thematic categories: LLM-Based Virtual Patient and Clinical Simulation Systems ( Conclusions: AI implementation in clinical skills education has accelerated substantially since 2022, with large language model-powered virtual patient simulations emerging as the predominant application. Current implementations primarily position AI as a supplementary formative tool rather than a replacement for established pedagogical approaches. Robust evidence regarding long-term educational impact remains limited, indicating need for rigorous longitudinal evaluation alongside continued innovation.
Indexed as
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What OpenQuestion 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 OpenQuestion graph.