Evidence map›Paper›PMID 42141085›Full record

ReviewNPJ digital medicine2026

AI-PACE: a framework for integrating AI into medical education.

Scott P McGrath, Katherine K Kim, Karnjit Johl, Haibo Wang, Nick Anderson

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in NPJ digital medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Scott P McGrathCenter for Information Technology in the Interest of Society, University of California Berkeley, Berkeley, CA, USA. smcgrath@berkeley.edu.
Katherine K KimSchool of Medicine, Department of Public Health Sciences, University of California Davis, Davis, CA, USA.
Karnjit JohlSchool of Medicine, Department of Internal Medicine, University of California Davis, Davis, CA, USA.
Haibo WangResearch Centre of Big Data and AI for Medicine First Affiliated Hospital of Sun Yan-Sen University Guangzhou, Guangzhou, China.
Nick AndersonSchool of Medicine, Department of Public Health Sciences, University of California Davis, Davis, CA, USA.

Funding

UC Davis Clinical and Translational Science CenterUL1TR001860 · NCATS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI KENYON, NICHOLAS J., LYLES, COURTNEY REES · 2016 to 2025
$47.3M
NCATS NIH HHS UL1 TR001860Surgical Robotics and Health Informatics Training Program, sponsored by The First Affiliated Hospital, Sun Yat-Sen University A25-2059-002
6 · The paper itself

Abstract

Medical AI education remains fragmented, specialty-skewed, and lacks longitudinal structure, particularly for generalist physicians. Through an integrative review of 23 peer-reviewed articles (2016-2025), we identified three structural gaps: short-term interventions without reinforcement, procedural-field bias, and consistent under-representation of the Affective domain. We present AI-PACE (Psychomotor, Affective, Cognitive, Embedded), a Bloom's Taxonomy-grounded framework organizing AI competencies longitudinally across undergraduate, graduate, and continuing medical education.

Identifiers

PMID42141085
PMCPMC13434227

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.