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Cited by 24

The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

Detection of fake papers in the era of artificial intelligence

Dadkhah, Mehdi, Oermann, Marilyn H., Hegedüs, Mihály, Raman, Raghu, Dávid, Lóránt Dénes·2023·Diagnosis
DOI 10.1515/dx-2023-0090
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Abstract

Objectives: Paper mills, companies that write scientific papers and gain acceptance for them, then sell authorships of these papers, present a key challenge in medicine and other healthcare fields. This challenge is becoming more acute with artificial intelligence (AI), where AI writes the manuscripts and then the paper mills sell the authorships of these papers. The aim of the current research is to provide a method for detecting fake papers. Methods: The method reported in this article uses a machine learning approach to create decision trees to identify fake papers. The data were collected from Web of Science and multiple journals in various fields. Results: The article presents a method to identify fake papers based on the results of decision trees. Use of this method in a case study indicated its effectiveness in identifying a fake paper. Conclusions: This method to identify fake papers is applicable for authors, editors, and publishers across fields to investigate a single paper or to conduct an analysis of a group of manuscripts. Clinicians and others can use this method to evaluate articles they find in a search to ensure they are not fake articles and instead report actual research that was peer reviewed prior to publication in a journal.

Overview

Integrity signals

Registry

Crossref · 10.1515/dx-2023-0090

Cites

5 of 5 references verified0 citation errors · 0 not checkable

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Claims other papers make about this one

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Citations

Cites

Show all 5 references

Research works printed but not linked: 32

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Metadata

Authors
Dadkhah, M., Oermann, M. H., Hegedüs, M., Raman, R., & Dávid, L. D.
Affiliations
  • Amrita School of Engineering , Amrita Vishwa Vidyapeetham , Amritapuri , Kerala , India
  • School of Nursing , Duke University , Durham , NC , USA
  • Tomori Pál College, Hungaryf Hungarian Auditors , Budapest , Hungary
  • Amrita School of Business , Amrita Vishwa Vidyapeetham , Amritapuri , Kerala , India
  • Faculty of Economics and Business , John von Neumann University , Kecskemet , Hungary
ORCID
Venue
Diagnosis
Publisher
Walter de Gruyter GmbH
Published
2023-08-17
Volume
10
Issue
4
Pages
390-397
ISSN
2194-802X
DOI
10.1515/dx-2023-0090
Cited by
24
References
5
Language
en

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