Evidence map›Paper›PMID 40353035›Full record

ArticleMedical science educator2025

Navigating the AI Revolution in Medicine-Adopting Strategies for Medical Education.

Colin Greengrass

Abstract read
In one paragraph

Article in Medical science educator, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Transforming Human-AI Collaboration in Emergency Care: The Role of AI in Adaptive Support Across Diagnostic Reasoning Modes.Academic emergency medicine : official journal of the Society for Academic Emergency Medicine · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. 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

1 author.

Colin GreengrassRoyal College of Surgeons in Ireland - Medical University of Bahrain, Adliya 15503, Bahrain.ORCID 0000-0002-5018-5109

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The integration of artificial intelligence (AI) into healthcare is set to fundamentally transform the role of medical professionals. This article takes a dive into the future specifying several strategies to prepare medical and other health professions students for an AI-driven healthcare system. It highlights the current and potential applications of AI in healthcare and discusses, in the immediate term, the necessity of incorporating AI education into medical curricula, including hands-on training and interdisciplinary collaboration. With a view to a more distant future, it also addresses probable ethical considerations, the evolving roles of healthcare professionals, a need for contingency and emphasises the importance of maintaining clinical skills amidst AI advancements. These strategies all aim to equip future medical graduates with competencies in knowledge, skills, and ethical grounding required to thrive in an AI-dominated healthcare environment. This framework is intended to stimulate discussion and provide a foundation upon which more detailed, context-specific strategies can be developed by educators, policymakers, and other stakeholders.

Indexed as

AI in clinical trainingArtificial intelligence in medical educationEthics of AI in healthcare educationIntegration of AI into the medical curriculum

Identifiers

PMID40353035
PMCPMC12058620

What OpenQuestion holds

Textmetadata
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.