Harnessing artificial intelligence for identifying conflicts of interest in research

doi:10.5662/wjm.v15.i1.98376

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World Journal of Methodology

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2222-0682

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

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World J Methodol. Mar 20, 2025; 15(1): 98376
Published online Mar 20, 2025. doi: 10.5662/wjm.v15.i1.98376

Harnessing artificial intelligence for identifying conflicts of interest in research

Abdulqadir J Nashwan

Abdulqadir J Nashwan, Department of Nursing & Midwifery Research, Hamad Medical Corporation, Doha 3050, Qatar

Author contributions: Nashwan AJ wrote and edited the manuscript, and conducted the literature review; the author has read and approved the final manuscript.

Conflict-of-interest statement: The author declares that he has no conflict of interest.

Corresponding author: Abdulqadir J Nashwan, MSc, PhD(c), Research Scientist, Department of Nursing & Midwifery Research, Hamad Medical Corporation, Rayyan Road, Doha 3050, Qatar. anashwan@hamad.qa

Received: June 25, 2024
Revised: August 5, 2024
Accepted: August 8, 2024
Published online: March 20, 2025
Processing time: 95 Days and 23.7 Hours

Abstract

This editorial explores the transformative potential of artificial intelligence (AI) in identifying conflicts of interest (COIs) within academic and scientific research. By harnessing advanced data analysis, pattern recognition, and natural language processing techniques, AI offers innovative solutions for enhancing transparency and integrity in research. This editorial discusses how AI can automatically detect COIs, integrate data from various sources, and streamline reporting processes, thereby maintaining the credibility of scientific findings.

Keywords: Artificial intelligence; Conflicts of interest; Transparency; Research integrity; Natural language processing

Core Tip: This editorial outlines the revolutionary role of artificial intelligence (AI) in detecting conflicts of interest (COIs) within academic and scientific communities. Utilizing sophisticated algorithms for data analysis, pattern recognition, and natural language processing, AI provides novel means to boost transparency and uphold integrity in research. The discussion extends to AI's capabilities to autonomously identify COIs, amalgamate diverse data streams, and simplify the reporting mechanisms, ensuring the reliability of scientific outputs.