Evidence map›Paper›PMID 40772076›Full record

ReviewJournal of education and health promotion2025

Impact of artificial intelligence on academic performance in medical education: A systematic review.

Masomeh Kalantarion, Mehrsa Heidari, Nasrin Khajeali, Zahra Khorrami, Mitra Amini

Abstract readReview
In one paragraph

Review in Journal of education and health promotion, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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

  1. Pooled it
  2. Review
  3. Review
  4. 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.

Masomeh KalantarionDepartment of Medical Education, School of Medical Education and Learning Technologies, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Mehrsa HeidariDepartment of Medicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
Nasrin KhajealiDepartment of Medical Education, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
Zahra KhorramiOphthalmic Epidemiology Research Center, Research Institute for Ophthalmology and Vision Science, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Mitra AminiClinical Education Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) plays a significant role in improving the quality of medical education. This study aimed to investigate the application of AI in medical education. A systematic review was conducted of all educational intervention studies in medical courses from January 1986 to 2023. Of the 16755 studies initially identified by our search, 7387 remained after removing duplicates. After that, 6205 studies were excluded for the title and abstract screening. Then, 15 full-text articles were included in our final review. The following keywords were used: artificial intelligence, machine intelligence, medical education, medical teaching, precision medical teaching, and precision medical education. A total of 16745 articles were identified from ISI, PubMed, Scopus, and Educational Resources and Information Center (ERIC) databases. Fourteen studies met the eligibility criteria. The quality of the included articles was appraised by the best evidence medical education (BEME) review of the education portfolio. PICO consists of

Indexed as

Artificial intelligenceaugmented realitieseducational technologiesmachine learningmedical educationvirtual reality

Identifiers

PMID40772076
PMCPMC12327735

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.