• Brain Predictability toolbox:...

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

Title:
Brain Predictability toolbox: a Python library for neuroimaging-based machine learning.
Authors:
Hahn S; Department of Psychiatry and Complex Systems, University of Vermont, Burlington, VT 05401, USA., Yuan K; Department of Psychiatry and Complex Systems, University of Vermont, Burlington, VT 05401, USA., Thompson WK; Division of Biostatistics, Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, CA 92093, USA., Owens M; Department of Psychiatry and Complex Systems, University of Vermont, Burlington, VT 05401, USA., Allgaier N; Department of Psychiatry and Complex Systems, University of Vermont, Burlington, VT 05401, USA., Garavan H; Department of Psychiatry and Complex Systems, University of Vermont, Burlington, VT 05401, USA.
Source:
Bioinformatics (Oxford, England) [Bioinformatics] 2021 Jul 12; Vol. 37 (11), pp. 1637-1638.
Publication Type:
Journal Article; Research Support, N.I.H., Extramural
Language:
English
Journal Info:
Publisher: Oxford University Press Country of Publication: England NLM ID: 9808944 Publication Model: Print Cited Medium: Internet ISSN: 1367-4811 (Electronic) Linking ISSN: 13674803 NLM ISO Abbreviation: Bioinformatics Subsets: MEDLINE
Imprint Name(s):
Original Publication: Oxford : Oxford University Press, c1998-
MeSH Terms:
Neuroimaging* , Software*, Brain/diagnostic imaging ; Gene Library ; Humans ; Machine Learning
References:
Bioinformatics. 2010 May 15;26(10):1340-7. (PMID: 20385727)
Front Neuroinform. 2014 Feb 21;8:14. (PMID: 24600388)
Grant Information:
R01 DA047119 United States DA NIDA NIH HHS; T32 DA043593 United States DA NIDA NIH HHS
Entry Date(s):
Date Created: 20201120 Date Completed: 20210715 Latest Revision: 20241116
Update Code:
20250114
PubMed Central ID:
PMC8485846
DOI:
10.1093/bioinformatics/btaa974
PMID:
33216147
Database:
MEDLINE

Weitere Informationen

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.
(© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)