Evidence map›Paper›PMID 37546190›Full record

ArticleMedical science educator2023

Biomedical Ethical Aspects Towards the Implementation of Artificial Intelligence in Medical Education.

Felix Busch, Lisa C Adams, Keno K Bressem

Abstract readEditorial
In one paragraph

Article in Medical science educator, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
–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

28 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. A Theoretical Framework forInfection and drug resistance · 2026
    Article
  9. Article
  10. A survey on ethical digital twins in healthcare.Frontiers in artificial intelligence · 2026
    Review
  11. Article
  12. Article
  13. Article
  14. Artificial Intelligence in Biomedical Sciences: A Scoping Review.British journal of biomedical science · 2025
    Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

3 authors.

Felix BuschDepartment of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany.ORCID 0000-0001-9770-8555
Lisa C Adams *Department of Radiology, Stanford University School of Medicine, Stanford, CA USA.ORCID 0000-0001-5836-4542
Keno K Bressem *Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany.ORCID 0000-0001-9249-8624

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The increasing use of artificial intelligence (AI) in medicine is associated with new ethical challenges and responsibilities. However, special considerations and concerns should be addressed when integrating AI applications into medical education, where healthcare, AI, and education ethics collide. This commentary explores the biomedical ethical responsibilities of medical institutions in incorporating AI applications into medical education by identifying potential concerns and limitations, with the goal of implementing applicable recommendations. The recommendations presented are intended to assist in developing institutional guidelines for the ethical use of AI for medical educators and students.

Indexed as

AIBiomedical ethicsChatGPTEducation, MedicalMachine learningPractice guidelines

Identifiers

PMID37546190
PMCPMC10403458

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.