Signature of Alzheimer disease

This work includes packages, scripts, and notebooks for the following article A signature of cognitive deficits and brain atrophy that is highly predictive of progression to Alzheimer’s dementia.

Here is a brief description of each item in the repository:

  • Proteus - a Python package by Christian Dansereau. Proteus was built on scikit-learn and it offers machine learning tools to make highly confident predictions
  • vcog_hpc_prediction_simulated_data.ipynb - a Jupyter notebook containing analyses that give a highly predictive signature (HPS) of Alzheimer’s disease dementia from cognitive and structural features using simulated data
  • - a Python script that generates simulated data from raw data
  • simulated_data.csv - a comma separated value file that contains simulated data
  • spm_container - an Octave package containing wrappers for SPM12 functions for segmentation and DARTEL

It is rendered here using Jupyter Book, with compute infrastructure provided by the Canadian Open Neuroscience Platform (CONP).