Karakuzu A, Boudreau M, Stikov N. Reproducible Research Practices in Magnetic Resonance Neuroimaging: A Review Informed by Advanced Language Models.
Magn Reson Med Sci 2024;
23:252-267. [PMID:
38897936 PMCID:
PMC11234949 DOI:
10.2463/mrms.rev.2023-0174]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/21/2024] Open
Abstract
MRI has progressed significantly with the introduction of advanced computational methods and novel imaging techniques, but their wider adoption hinges on their reproducibility. This concise review synthesizes reproducible research insights from recent MRI articles to examine the current state of reproducibility in neuroimaging, highlighting key trends and challenges. It also provides a custom generative pretrained transformer (GPT) model, designed specifically for aiding in an automated analysis and synthesis of information pertaining to the reproducibility insights associated with the articles at the core of this review.
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