Fraud in Medical Publications.
Artificial intelligence
Fabrication
Fraud
Research
Retraction
Journal
Anesthesiology clinics
ISSN: 1932-2275
Titre abrégé: Anesthesiol Clin
Pays: United States
ID NLM: 101273663
Informations de publication
Date de publication:
Dec 2024
Dec 2024
Historique:
medline:
24
10
2024
pubmed:
24
10
2024
entrez:
23
10
2024
Statut:
ppublish
Résumé
This review highlights the increasing prevalence of fraudulent data and publications in medical research, emphasizing the potential harm to patients and the erosion of trust in the medical community. It discusses the impact of low-quality studies on clinical guidelines and patient safety, emphasizing the need for prompt identification. The review proposes using machine learning and artificial intelligence as potential tools to detect anomalies, plagiarism, and data manipulation, potentially improving the peer review process. Despite the acknowledgment of this problem and the growing number of retractions, the review notes a lack of focus on the clinical implications of forged evidence.
Identifiants
pubmed: 39443033
pii: S1932-2275(24)00012-0
doi: 10.1016/j.anclin.2024.02.004
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
607-616Informations de copyright
Copyright © 2024 Elsevier Inc. All rights reserved.
Déclaration de conflit d'intérêts
Disclosure C. Gianluca Nato has nothing to disclose. F. Bilotta has nothing to disclose.