Evidence map›Paper›PMID 40576330›Full record

ArticleInternal medicine journal2025

Proposing core competencies for physicians in using artificial intelligence tools in clinical practice.

Ian A Scott, Tim Shaw, Christine Slade, Tai Tak Wan, Rahul Barmanray, Craig Coorey, Sandra Lj Johnson, Lana Bell, Michael Herd, Clair M Sullivan

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Internal medicine journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. AI Competency: Current State and Challenges.JMIR medical education · 2026
    Article
  3. Article
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

10 authors.

Ian A ScottDigital Health and Informatics, Metro South Hospital and Health Service, Brisbane, Queensland, Australia.ORCID 0000-0002-7596-0837
Tim ShawFaculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia.
Christine SladeInstitute for Teaching and Learning Innovation (ITaLI), University of Queensland, Brisbane, Queensland, Australia.
Tai Tak WanAmbulatory Care, Fairfield Hospital, Prairiewood, New South Wales, Australia.
Rahul BarmanrayGeneral Medicine, The Royal Melbourne Hospital, Melbourne, Victoria, Australia.
Craig CooreyRenal Medicine, Royal Prince Alfred Hospital, Sydney, New South Wales, Australia.
Sandra Lj JohnsonPrivate Practice, Sydney, New South Wales, Australia.
Lana BellJoondalup Specialist Centre, Joondalup Health Campus, Joondalup, Western Australia, Australia.
Michael HerdPaediatrics and Child Health, Whakatane Hospital, Whakatane, New Zealand.
Clair M SullivanQueensland Digital Health Centre, University of Queensland, Brisbane, Queensland, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) will likely transform many aspects of healthcare, and physicians will need to adapt and lead. The expanding range of AI tools calls for physicians to become competent in their proper use if we are to achieve better patient experience, population health and health equity, and with greater efficiency, while enhancing physician satisfaction. This viewpoint proposes a practical and manageable set of core competencies for physicians in using AI tools effectively and ethically and suggests methods for acquiring these competencies.

Indexed as

Artificial IntelligenceClinical CompetencePhysiciansHumansartificial intelligenceclinical practicecompetenciescorephysicians

Identifiers

PMID40576330
PMCPMC12347303

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.