This repository contains the code for the paper Autism Classification Using Topological Features and Deep Learning: A Cautionary Tale.
The driver code can be found in src/Experiments.ipynb - it contains the code to load the
dataset, extract features, define and evalaute models.
The code is written for Python 3.7 and has been tested with the following package configuration. Older versions of the package may work but I haven't tested those.
numpy==1.18.5
tqdm==4.47.0
sklearn==0.23.1
skorch==0.8.0
ripser==0.3.2
sklearn_tda # https://github.com/MathieuCarriere/sklearn-tda
torch==1.2.0
pandas==0.25.1
scipy==1.5.0
statsmodels==0.11.1
If you find this code useful, please cite our paper:
@inproceedings{RathorePalandeWang2019,
title={Autism Classification Using Topological Features and Deep Learning: A Cautionary Tale},
author={Rathore, Archit and Palande, Sourabh and Anderson, Jeffrey S and Zielinski, Brandon A and Fletcher, P Thomas and Wang, Bei},
booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
pages={736--744},
year={2019},
organization={Springer}
}