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阅读障碍数据联盟存储库:一个数据共享和交付平台,用于研究

Roshan Bhandari¹, Rishikesh V Phatangare¹, Mark A Eckert²

¹School of Computing, Clemson University, Clemson, SC, USA.

Brain informatics : 16th International Conference, BI 2023, Hoboken, NJ, USA, August 1-3, 2023, Proceedings. International Conference on Brain Informatics (16th : 2023 : Hoboken, N.J.)

|February 14, 2024

概括

一个新的在线平台,DyslexiaData.org,通过分享神经成像数据和机器学习工具,为阅读障碍研究提供开放科学. 本资源旨在促进对阅读障碍的理解,并支持未来的科学发现.

科学领域:

神经科学是一个神经科学.
发展心理学发展心理学
计算生物学计算生物学

背景情况:

阅读障碍影响美国人口的5-17%,在神经生物学研究中存在挑战,因为样本大小小小,多个地点.
数据的有限可访问性阻碍了像深度学习这样的先进方法在阅读障碍研究中的应用.

研究的目的:

建立一个开放访问的在线平台 (DyslexiaData.org) 用于数据共享和阅读障碍的先进研究.
为研究人员提供二次数据集和工具,以增强复制和培养新的研究方法.

主要方法:

开发一个集成的在线平台,具有数据共享功能.
实现机器学习算法来生成二次数据集 (例如皮质厚度,区域大脑体积).

主要成果:

该平台提供了与阅读障碍相关的神经生物学数据的访问权限.
促进对高级研究应用的二次数据集的生成.

结论:

DyslexiaData.org旨在通过促进开放科学和数据可访问性来克服当前阅读障碍研究的局限性.
该平台将支持基础研究,复制研究和未来研究人员的教育,最终促进对阅读障碍的理解.

关键词:

数据质量评估数据质量评估深度学习 (Deep Learning) 是一种深度学习.阅读障碍症数据联盟神经成像数据集是指神经成像数据集.隐私保护隐私保护隐私保护

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