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Brain Predictability toolbox: a Python library for neuroimaging based machine learning

Authors :
Hahn, Sage
Yuan, Dekang
Thompson, Wesley
Owens, Max M
Allgaier, Nicholas
Garavan, Hugh
Publication Year :
2020

Abstract

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<br />Comment: 3 Pages

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2011.01715
Document Type :
Working Paper