Evidence map›Paper›PMID 40509539›Full record

ArticleHemodialysis international. International Symposium on Home Hemodialysis2025

Use of Artificial Intelligence in Scientific Writing. The Danger of Trying Too Hard to Please.

John T Daugirdas

Abstract read
In one paragraph

Article in Hemodialysis international. International Symposium on Home Hemodialysis, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Use of Artificial Intelligence in Scientific Writing. The Danger of Trying Too Hard to Please.Hemodialysis international. International Symposium on Home Hemodialysis · 2025
    Article
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

1 author.

John T DaugirdasUniversity of Illinois at Chicago College of Medicine, Chicago, Illinois, USA.ORCID https://orcid.org/0000-0002-0644-6842

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The author describes his experience using several artificial intelligence programs to assist in the process of editing or preparing manuscripts for publication. While the programs were very useful to increase clarity and optimize the English of previously written text, problems arose when asked to review the literature to describe or expand on concepts, and then to cite references to support those statements. Citations were sometimes fabricated. The artificial intelligence program would even provide PubMed identification (PMID) numbers for references cited, which sometimes pointed to completely different publications. In references that were correctly cited, a request to extract data from their abstracts yielded data that were completely fabricated or incorrect. The newer versions of these artificial intelligence programs appear to be enormously helpful in helping with the process of scientific writing, but one needs to assiduously verify every statement made with regard to their interpretation of the medical literature and double-check any citations by retrieving and reading those references. Because statements made by these agents are proffered with great confidence and using excellent writing skills, the resulting errors can be difficult to anticipate. The motivations behind such errors are unknown, but appear to be related to a desire of AI to please the user at any cost. Programmers who create these tools somehow managed to allow such errors, and this issue must be addressed in future versions of AI. Also, it would help greatly if AI had access to the full text of medical scientific articles, which might be achieved by contractual agreements with the main medical publishers.

Indexed as

Artificial IntelligenceWritingHumans

Identifiers

PMID40509539
PMCPMC12531926

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.