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

Agah Karakuzu, Mathieu Boudreau, Nikola Stikov
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引用次数: 0

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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磁共振神经成像中的可重复研究实践:以高级语言模型为基础的综述。
随着先进计算方法和新型成像技术的引入,核磁共振成像技术取得了长足的进步,但它们能否被更广泛地采用取决于其可重复性。这篇简明综述综合了近期核磁共振成像文章中的可重复性研究观点,探讨了神经成像的可重复性现状,强调了主要趋势和挑战。它还提供了一个定制的生成预训练变换器(GPT)模型,专门用于帮助自动分析和综合与本综述核心文章相关的可重复性见解有关的信息。
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