Evidence map›Paper›PMID 41970089›Full record

ArticleCureus2026

Publishing in the Era of Artificial Intelligence: What Do Medical Research Journals Expect?

Irrum Afzal, Sarkhell Radha

Abstract readEditorial
In one paragraph

Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Irrum AfzalTrauma and Orthopaedics, Croydon University Hospital, London, GBR.
Sarkhell RadhaTrauma and Orthopaedics, Croydon University Hospital, London, GBR.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) is now embedded across medical research and practice, reshaping how evidence is generated and evaluated. Rather than lowering standards, AI has intensified editorial expectations within medical journals. Editors prioritise clinically meaningful knowledge over technical novelty, demanding a clear demonstration of how AI augments clinical reasoning and improves patient outcomes. Transparency in AI use, rigorous methodology, bias assessment, and external validation are increasingly essential. As generative AI normalises polished writing, originality is judged by intellectual and clinical contribution rather than style. Ultimately, journals seek responsible, reproducible, and ethically grounded AI-enabled research that advances patient care and public trust.

Indexed as

artificial intelligenceartificial intelligence in medicinemedical researchpublishingresearch & development

Identifiers

PMID41970089
PMCPMC13065253

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.