From 37d8d96a08d17bda65353715b0de5028ad918aac Mon Sep 17 00:00:00 2001 From: Mauricio DIAZ Date: Thu, 17 Oct 2019 00:13:17 +0200 Subject: [PATCH] Add information to README Former-commit-id: 22ba11eddbecbc59e562a76784aba01e00327d6f --- README.md | 19 +++++++++++-------- 1 file changed, 11 insertions(+), 8 deletions(-) diff --git a/README.md b/README.md index 9a354b6b0..290a02c94 100755 --- a/README.md +++ b/README.md @@ -3,7 +3,8 @@ This repository contains a software framework for reproducible experiments with convolutional neural networks on automatic classification of Alzheimer's disease (AD) using anatomical MRI data from the publicly available dataset ADNI. It is developed by Junhao WEN, Elina Thibeau--Sutre and Mauricio Diaz. -The preprint of the corresponding paper may be found [here](https://arxiv.org/abs/1904.07773) +The preprint version of the corresponding paper may be found +[here].(https://arxiv.org/abs/1904.07773) Automatic Classification of AD using a classical machine learning approach can be performed using the software available here: @@ -18,10 +19,13 @@ All the papers described in the State of the art section of the manuscript may be found at this URL address: . - # Dependencies: - Python >= 3.6 -- Clinica (needs to perform preprocessing) +- Clinica (needs only to perform preprocessing) +- Numpy +- Pandas +- Scikit-learn +- Pandas - Pytorch - Nilearn - Nipy @@ -145,10 +149,9 @@ optional arguments: ``` ## Or use the scripts +Look at the `clinicadl/scripts/` folder. + +# Run testing: ``` -python run_train.py --max_steps 10000 --dropout_rate 0.2 -``` -# run testing: -``` -python run_test.py +pytest clinicadl/tests/ ```