脑可预测性工具包：一个基于神经影像学的机器学习的 Python 库。
Brain Predictability toolbox: a Python library for neuroimaging-based machine learning.
机构信息
Department of Psychiatry and Complex Systems, University of Vermont, Burlington, VT 05401, USA.
Division of Biostatistics, Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, CA 92093, USA.
出版信息
Bioinformatics. 2021 Jul 12;37(11):1637-1638. doi: 10.1093/bioinformatics/btaa974.
SUMMARY
Brain Predictability toolbox (BPt) represents a unified framework of machine learning (ML) tools designed to work with both tabulated data (e.g. brain derived, psychiatric, behavioral and physiological variables) and neuroimaging specific 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.
摘要
脑可预测性工具包 (BPt) 代表了一个统一的机器学习 (ML) 工具框架，旨在同时处理表格数据（例如大脑衍生、精神科、行为和生理变量）和神经影像学特定数据（例如大脑体积和表面）。这个软件包适用于研究各种不同的基于神经影像学的 ML 问题，特别是那些从大型人类数据集查询的问题。
可用性和实现
BPt 已作为一个开源 Python 3.6+ 软件包在 https://github.com/sahahn/BPt 上开发，遵循 MIT 许可证，文档在 https://bpt.readthedocs.io/en/latest/ 提供，并在持续积极开发中。该项目可以通过提供的 github 链接下载。一个基于相同代码的网络 GUI 界面正在开发中，可以通过在 https://github.com/sahahn/BPt_app 上的说明使用 docker 设置。
Zotero 插件