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神经影像工具箱的模式识别

Pattern Recognition for Neuroimaging Toolbox
课程网址: http://videolectures.net/machine_schrouff_pattern_recognition/  
主讲教师: Jessica Schrouff
开课单位: 列日大学
开课时间: 2013-08-06
课程语种: 英语
中文简介:
在过去几年中,通过使用多变量模式分析,特别是基于机器学习模型,补充了神经成像数据的大规模单变量统计分析。虽然与单变量技术相比,这些可以提高检测空间分布效应的灵敏度,但它们缺乏既定且可访问的软件框架。这项工作的目标是基于机器学习模型构建一个工具箱,其中包含神经影像数据多变量分析的所有必要功能。 “神经影像工具箱的模式识别”(PRoNTo)是开源,跨平台和基于MATLAB的,因此适用于认知和临床神经科学研究。此外,它旨在促进开发人员的新颖贡献,旨在改善神经影像学和机器学习社区之间的互动。
课程简介: In the past years, mass univariate statistical analyses of neuroimaging data have been complemented by the use of multivariate pattern analyses, especially based on machine learning models. While these allow an increased sensitivity for the detection of spatially distributed effects compared to univariate techniques, they lack an established and accessible software framework. The goal of this work was to build a toolbox comprising all the necessary functionalities for multivariate analyses of neuroimaging data, based on machine learning models. The “Pattern Recognition for Neuroimaging Toolbox” (PRoNTo) is open-source, cross-platform and MATLAB-based, therefore being suitable for both cognitive and clinical neuroscience research. In addition, it is designed to facilitate novel contributions from developers, aiming to improve the interaction between the neuroimaging and machine learning communities.
关 键 词: 多变量模式; 机器学习; 神经成像数据
课程来源: 视频讲座网
最后编审: 2019-05-15:lxf
阅读次数: 107