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

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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… Click to show full abstract

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.

Keywords: machine learning; bpt; brain predictability; neuroimaging based; brain; predictability toolbox

Journal Title: Bioinformatics
Year Published: 2021

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