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Federating Heterogeneous Datasets to Enhance Data Sharing and Experiment Reproducibility

机译:联合异构数据集以增强数据共享和实验可重复性

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摘要

Recent studies have demonstrated the difficulties to replicate scientific findings and/or experiments published in past. The effects seen in the replicated experiments were smaller than previously reported. Some of the explanations for these findings include the complexity of the experimental design and the pressure on researches to report positive findings. The International Committee of Medical Journal Editors (ICMJE) suggests that every study considered for publication must submit a plan to share the de-identified patient data no later than 6 months after publication. There is a growing demand to enhance the management of clinical data, facilitate data sharing across institutions and also to keep track of the data from previous experiments. The ultimate goal is to assure the reproducibility of experiments in the future. This paper describes Shiny-tooth, a web based application created to improve clinical data acquisition during the clinical trial; data federation of such data as well as morphological data derived from medical images; Currently, this application is being used to store clinical data from an osteoarthritis (OA) study. This work is submitted to the SPIE Biomedical Applications in Molecular, Structural, and Functional Imaging conference.
机译:最近的研究表明,难以复制过去发表的科学发现和/或实验。 在复制的实验中看到的效果比以前报道的要小。对这些发现的一些解释包括实验设计的复杂性以及研究报告积极发现的压力。国际医学杂志编辑委员会(ICMJE)建议,考虑发表的每项研究都必须提交计划,以在发表后至少6个月内共享已识别身份的患者数据。越来越需要加强临床数据的管理,促进跨机构的数据共享以及跟踪先前实验的数据。最终目标是确保将来实验的可重复性。本文介绍了Shiny-tooth,这是一个基于Web的应用程序,旨在改善临床试验期间的临床数据获取。这些数据以及从医学图像得出的形态数据的数据联合;当前,该应用程序用于存储来自骨关节炎(OA)研究的临床数据。这项工作已提交给SPIE分子,结构和功能成像的生物医学应用会议。

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