论文标题
大脑可预测性工具箱：用于基于神经成像的机器学习的Python库
Brain Predictability toolbox: a Python library for neuroimaging based machine learning
论文作者
论文摘要
摘要大脑可预测性工具箱（BPT）代表了机器学习的统一框架（ML）工具，旨在与列表的数据（尤其是大脑，精神病，行为和生理变量）和神经成像数据（例如，大脑，精神病学，行为和生理变量）一起使用。该软件包适合研究广泛的基于神经影像学的ML问题，特别是从大型人类数据集中查询的问题。 可用性和实施BPT已被开发为在https://github.com/sahahn/bpt托管的开源python 3.6+软件包经MIT许可下，并在https://bpt.readthedocs.io/en/latest/上提供了文档，并继续进行了积极开发。该项目可以通过提供的GitHub链接下载。当前正在开发基于相同代码的Web GUI界面，可以通过Docker在https://github.com/sahahn/bpt_app上通过Docker进行设置。 请联系[email protected]与Sage Hahn联系
Summary Brain Predictability toolbox (BPt) represents a unified framework of machine learning (ML) tools designed to work with both tabulated data (in particular brain, psychiatric, behavioral, and physiological variables) and neuroimaging specific derived data (e.g., brain volumes and surfaces). This package is suitable for investigating a wide range of different neuroimaging based ML questions, in particular, those queried from large human datasets. Availability and Implementation BPt has been developed as an open-source Python 3.6+ package hosted at https://github.com/sahahn/BPt under MIT License, with documentation provided at https://bpt.readthedocs.io/en/latest/, and continues to be actively developed. The project can be downloaded through the github link provided. A web GUI interface based on the same code is currently under development and can be set up through docker with instructions at https://github.com/sahahn/BPt_app. Contact Please contact Sage Hahn at [email protected]
