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磁共振神经影像学中的可重复性研究实践:基于先进语言模型的综述。

Reproducible Research Practices in Magnetic Resonance Neuroimaging: A Review Informed by Advanced Language Models.

机构信息

NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montréal, Montréal, Quebec, Canada.

Montréal Heart Institute, Montréal, Quebec, Canada.

出版信息

Magn Reson Med Sci. 2024 Jul 1;23(3):252-267. doi: 10.2463/mrms.rev.2023-0174. Epub 2024 Jun 19.

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.

摘要

MRI 随着先进计算方法和新型成像技术的引入取得了重大进展,但它们的广泛应用取决于其可重复性。这篇简明综述综合了最近 MRI 文章中的可重复性研究见解,以检查神经影像学中的可重复性现状,突出关键趋势和挑战。它还提供了一个定制的生成式预训练转换器 (GPT) 模型,专门用于辅助对本综述核心文章中与可重复性见解相关的信息进行自动分析和综合。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a670/11234949/167c646bc7bb/mrms-23-252-g1.jpg

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