Evidence map›Paper›PMID 37038381›Full record

ReviewCureus2023

Overview of Early ChatGPT's Presence in Medical Literature: Insights From a Hybrid Literature Review by ChatGPT and Human Experts.

Omar Temsah, Samina A Khan, Yazan Chaiah, Abdulrahman Senjab, Khalid Alhasan, Amr Jamal, Fadi Aljamaan, Khalid H Malki, Rabih Halwani, Jaffar A Al-Tawfiq and 2 more

Abstract readReview
In one paragraph

Review in Cureus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
72citing papers in PubMed, 2 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

72 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  7. Review
  8. The Application of Flipped Classroom Integrated with ChatGPT in Improving Graduate Education on Choroidal Melanoma.Journal of cancer education : the official journal of the American Association for Cancer Education · 2025
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12 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

12 authors.

Omar TemsahCollage of Medicine, Alfaisal University, Riyadh, SAU.
Samina A KhanComputer Sciences, Universiti Sains Malaysia, Penang, MYS.
Yazan ChaiahCollege of Medicine, Alfaisal University, Riyadh, SAU.
Abdulrahman SenjabCollege of Medicine, Alfaisal University, Riyadh, SAU.
Khalid AlhasanPediatric Nephrology, King Saud University, Riyadh, SAU.
Amr JamalFamily and Community Medicine, King Saud University, Riyadh, SAU.
Fadi AljamaanCritical Care, King Saud University, Riyadh, SAU.
Khalid H MalkiOtolaryngology, King Saud University, Riyadh, SAU.
Rabih HalwaniClinical Sciences, University of Sharjah, Sharjah, ARE.
Jaffar A Al-TawfiqSpecialty Internal Medicine and Quality, Johns Hopkins Aramco Healthcare, Dhahran, SAU.
Mohamad-Hani TemsahPediatric Intensive Care, King Saud University, Riyadh, SAU.
Ayman Al-EyadhyPediatric Intensive Care, King Saud University, Riyadh, SAU.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

ChatGPT, an artificial intelligence chatbot, has rapidly gained prominence in various domains, including medical education and healthcare literature. This hybrid narrative review, conducted collaboratively by human authors and ChatGPT, aims to summarize and synthesize the current knowledge of ChatGPT in the indexed medical literature during its initial four months. A search strategy was employed in PubMed and EuropePMC databases, yielding 65 and 110 papers, respectively. These papers focused on ChatGPT's impact on medical education, scientific research, medical writing, ethical considerations, diagnostic decision-making, automation potential, and criticisms. The findings indicate a growing body of literature on ChatGPT's applications and implications in healthcare, highlighting the need for further research to assess its effectiveness and ethical concerns.

Indexed as

artificial intelligence in medicinechatgptdiagnostic decision-makingethical considerationsgenerative language modelhybrid methodmachine learning (ml)medical educationmedical practicemedical writing

Identifiers

PMID37038381
PMCPMC10082551

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.