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https://github.com/aramis-lab/ad-ml

Framework for the reproducible classification of Alzheimer's disease using machine learning

https://github.com/aramis-lab/ad-ml

Science Score: 13.0%

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Keywords

alzheimer-disease machine-learning neuroimaging python scikit-learn
Last synced: 7 months ago · JSON representation

Repository

Framework for the reproducible classification of Alzheimer's disease using machine learning

Basic Info
  • Host: GitHub
  • Owner: aramis-lab
  • License: mit
  • Language: Python
  • Default Branch: master
  • Homepage:
  • Size: 3.3 MB
Statistics
  • Stars: 41
  • Watchers: 6
  • Forks: 14
  • Open Issues: 1
  • Releases: 0
Topics
alzheimer-disease machine-learning neuroimaging python scikit-learn
Created almost 7 years ago · Last pushed almost 4 years ago
Metadata Files
Readme License

README.md

This repository contains a software framework for reproducible machine learning experiments on automatic classification of Alzheimer's disease (AD) using multimodal MRI and PET data from three publicly available datasets ADNI, AIBL, OASIS. It is developed by the ARAMIS Lab.

In the directory Generic Version, there are examples of data conversion, preprocessing and classification tasks, that show how to use the different features of Clinica software. This code relies on the latest released version of Clinica.

If you are interested in accessing the repositories containing the code of the experiments and results of our papers that use Clinica, please change to the branch of the corresponding paper:

Citing this work

If you use this software, please cite:

J. Samper-Gonzalez, N. Burgos, S. Bottani, S. Fontanella, P. Lu, A. Marcoux, A. Routier, J. Guillon, M. Bacci, J. Wen, A. Bertrand, H. Bertin, M.-O. Habert, S. Durrleman, T. Evgeniou and O. Colliot, Reproducible evaluation of classification methods in Alzheimer's disease: Framework and application to MRI and PET data. NeuroImage, 183:504–521, 2018 doi:10.1016/j.neuroimage.2018.08.042 - Paper in PDF - Supplementary material

In addition, if you use Diffusion MRI data or related code, please cite:

J. Wen, J. Samper-Gonzalez, S. Bottani, A. Routier, N. Burgos, T. Jacquemont, S. Fontanella, S. Durrleman, S. Epelbaum, A. Bertrand, and O. Colliot, Reproducible evaluation of diffusion MRI features for automatic classification of patients with Alzheimer’s disease. Submitted for publication

Documentation

This code relies heavily on the Clinica software platform that you will need to install.

The documentation is available at: https://github.com/aramis-lab/AD-ML/wiki

Owner

  • Name: ARAMIS Lab
  • Login: aramis-lab
  • Kind: organization
  • Location: Paris, France

The Aramis Lab is a joint research team between CNRS, Inria, Inserm and Sorbonne University and belongs to the Paris Brain Institute (ICM).

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Last synced: 8 months ago