Brain Predictability toolbox：一个基于神经成像的机器学习Python库
Brain Predictability toolbox: a Python library for neuroimaging based machine learning
摘要：
大脑可预测性工具箱（BPt）表示机器学习（ML）工具的统一框架，其被设计为与表格数据（特别是大脑、精神、行为和生理变量）和神经成像特定的衍生数据（例如，脑体积和表面）。该软件包适用于研究各种不同的基于神经成像的ML问题，特别是那些从大型人类数据集查询的问题。可用性和实施BPt已开发为开源Python 3.6+包，托管在https://github.com/sahahn/BPt上，根据MIT许可证，文档在https：//bpt.readthedocs.io/en/latest/提供，并继续积极开发。该项目可以通过提供的github链接下载。基于相同代码的Web GUI界面目前正在开发中，可以通过docker进行设置，说明见https://github.com/sahahn/BPt_app。联系方式请联系Sage Hahn，网址为sahahn@uvm.edu
英文摘要：
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 sahahn@uvm.edu
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
