Evidence map›Paper›PMID 34250242›Full record

ArticleJournal of medical education and curricular development

Are We Ready to Integrate Artificial Intelligence Literacy into Medical School Curriculum: Students and Faculty Survey.

Elena A Wood, Brittany L Ange, D Douglas Miller

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of medical education and curricular development. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 104 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
104citing papers in PubMed, 5 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

104 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Attitudes and Knowledge Levels of Optometry Students and Educators Towards Artificial Intelligence in Optometric Practice: An Online Cross-Sectional Survey.Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists) · 2026
    Article

44 more citing papers are in PubMed but not listed here.

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.

Elena A WoodMedical College of Georgia at Augusta University, USA.ORCID https://orcid.org/0000-0003-1231-8473
Brittany L AngeMedical College of Georgia at Augusta University, USA.
D Douglas MillerMedical College of Georgia at Augusta University, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe effects of Artificial Intelligence (AI) technology applications are already felt in healthcare in general and in the practice of medicine in the disciplines of radiology, pathology, ophthalmology, and oncology. The expanding interface between digital data science, emerging AI technologies and healthcare is creating a demand for AI technology literacy in health professions.

objectiveTo assess medical student and faculty attitudes toward AI, in preparation for teaching AI foundations and data science applications in clinical practice in an integrated medical education curriculum.

methodsAn online 15-question semi-structured survey was distributed among medical students and faculty. The questionnaire consisted of 3 parts: participant's background, AI awareness, and attitudes toward AI applications in medicine.

resultsA total of 121 medical students and 52 clinical faculty completed the survey. Only 30% of students and 50% of faculty responded that they were aware of AI topics in medicine. The majority of students (72%) and faculty (59%) learned about AI from the media. Faculty were more likely to report that they did not have a basic understanding of AI technologies (χ

conclusionsThe survey conclusively proved interest among medical students and faculty in AI technology in general, and in its applications in healthcare and medicine. The study was conducted at a single institution. This survey serves as a foundation for other medical schools interested in developing a collaborative programming approach to address AI literacy in medical education.

Indexed as

AIArtificial intelligencemedical studentssurveyteaching facultyundergraduate medical education

Identifiers

PMID34250242
PMCPMC8239949

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.