ArticleThe American surgeon2024
The Utilization of ChatGPT in Reshaping Future Medical Education and Learning Perspectives: A Curse or a Blessing?
Article in The American surgeon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It carries an expression of concern. Cited by 7 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Ethical and practical challenges of generative AI in healthcare and proposed solutions: a survey.Frontiers in digital health · 2025Pooled it
- Reimagining pharmacology education.Pharmacological reviews · 2026Review
- Large language models as educational collaborators: developing non-conventional teaching aids in pharmacology & therapeutics.BMC medical education · 2025Article
- "I can no longer give take-home exams": Health professionals educators' experiences and perceptions regarding the use of artificial intelligence in health professions education in Uganda.BMC medical education · 2025Article
- ChatGPT and Other Large Language Models in Medical Education - Scoping Literature Review.Medical science educator · 2025Review
- Enhancing AI competence in health management: students' experiences with ChatGPT as a learning Tool.BMC medical education · 2024Article
- Artificial Intelligence-Prompted Explanations of Common Primary Care Diagnoses.PRiMER (Leawood, Kan.) · 2024Article
Corrections and comments
- Expression of concern
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundChatGPT has substantial potential to revolutionize medical education. We aim to assess how medical students and laypeople evaluate information produced by ChatGPT compared to an evidence-based resource on the diagnosis and management of 5 common surgical conditions.
methodsA 60-question anonymous online survey was distributed to third- and fourth-year U.S. medical students and laypeople to evaluate articles produced by ChatGPT and an evidence-based source on clarity, relevance, reliability, validity, organization, and comprehensiveness. Participants received 2 blinded articles, 1 from each source, for each surgical condition. Paired-sample t-tests were used to compare ratings between the 2 sources.
resultsOf 56 survey participants, 50.9% (n = 28) were U.S. medical students and 49.1% (n = 27) were from the general population. Medical students reported that ChatGPT articles displayed significantly more clarity (appendicitis: 4.39 vs 3.89,
conclusionMedical students perceived ChatGPT articles to be clearer and better organized than evidence-based sources on the pathogenesis, diagnosis, and management of 5 common surgical pathologies. However, evidence-based articles were rated as significantly more comprehensive.
Indexed as
Identifiers
37309705What OpenQuestion holds
Registered trials
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.