Evidence map›Paper›PMID 41250649›Full record

ArticleJournal of Korean medical science2025

Analysis of Retracted Publications on Artificial Intelligence: Trends, Ethical Concerns, and Scientific Integrity.

Burhan Fatih Kocyigit, Ramazan Azim Okyay, Birzhan Seiil, Ainur B Qumar, Hilmi Erdem Sumbul

Abstract read
In one paragraph

Article in Journal of Korean medical science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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

5 authors.

Burhan Fatih KocyigitDepartment of Physical Medicine and Rehabilitation, University of Health Sciences, Adana City Research and Training Hospital, Adana, Türkiye. bfk2701@hotmail.com.ORCID https://orcid.org/0000-0002-6065-8002
Ramazan Azim OkyayDepartment of Public Health, Faculty of Medicine, Kahramanmaraş Sütçü İmam University, Kahramanmaraş, Türkiye.ORCID https://orcid.org/0000-0001-8767-2771
Birzhan SeiilDepartment of Chemical Disciplines, Biology and Biochemistry, South Kazakhstan Medical Academy, Shymkent, Kazakhstan.ORCID https://orcid.org/0000-0003-1524-8888
Ainur B QumarDepartment of Health Policy and Management, Asfendiyarov Kazakh National Medical University, Almaty, Kazakhstan.ORCID https://orcid.org/0000-0003-0457-7205
Hilmi Erdem SumbulDepartment of Internal Medicine, University of Health Sciences, Adana Health Practice and Research Center, Adana, Türkiye.ORCID https://orcid.org/0000-0002-7192-0280

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArtificial intelligence (AI) has promoted progress across various fields. The number of papers regarding AI has risen in recent years. This study examines retracted publications regarding AI by analyzing trends, journals, and reasons.

methodsThis descriptive cross-sectional study thoroughly investigated retracted AI-related papers listed in PubMed. The data extraction comprised bibliographic data, reasons for retraction, citation metrics, journal indexing status, and Altmetric Attention Scores (AASs). Retraction notices were classified according to particular reasons. Descriptive statistics were employed to evaluate retraction trends, geographic distribution, and citation impact.

resultsA total of 764 retracted AI-related papers were examined, with the most retractions occurring in 2023 (n = 667). China had the highest number (n = 551), followed by India (n = 40) and Bangladesh (n = 23). Journals focusing on mathematical and computational biology, neurosciences, and healthcare sciences had the most retractions. The most common retraction reasons were peer review issues (n = 716) and data concerns (n = 714), followed by irrelevant citations (n = 571) and unethical AI use (n = 238). The median time to retraction was 510 days (18-4,200). The median citation and AAS scores were (0-167) and 0 (0-191).

conclusionThe high number of retractions from China highlights the need for higher research standards. Deficits in peer review and data issues emerged as the main reasons for retraction, underscoring persistent challenges in maintaining research integrity and quality assurance. For scientific literature integrity, academic institutions, publishers, and researchers should stress transparency, ethics, and rigorous post-publication inspection.

Indexed as

Artificial IntelligenceRetraction of Publication as TopicChinaCross-Sectional StudiesHumansArtificial IntelligenceDeep LearningMachine LearningRetraction NoticeRetraction of PublicationScientific Misconduct

Identifiers

PMID41250649
PMCPMC12624210

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.