s41467-020-20655-6

Reproducible Example Code (reprex) https://github.com/aabrol/SMLvsDL/tree/master/reprex

Reprex DL Classification/Regression Scripts
Slurm script - https://github.com/aabrol/SMLvsDL/tree/master/reprex/JSA_DL.sh
Bash for python script - https://github.com/aabrol/SMLvsDL/tree/master/reprex/run_DL.sh
Python script - https://github.com/aabrol/SMLvsDL/tree/master/reprex/run_DL.py
Utilies - https://github.com/aabrol/SMLvsDL/tree/master/reprex/utils.py
DL Model - https://github.com/aabrol/SMLvsDL/tree/master/reprex/models.py
Conda Environment - https://github.com/aabrol/SMLvsDL/tree/master/reprex/AA_DL.yml

Detailed (previous) version

Package Dependencies

conda (version 4.8.3) cudatoolkit (version 10.0.13) cudnn (version 7.6.5)
h5py (version 2.9.0) hdf5 (version 1.10.4) hypopt (version 1.0.9)
nipy (version 0.4.1) numpy (version 1.17.2) nibabel (version 2.5.0)
pandas (version 0.25.1) python (version 3.7.4) pytorch (version 1.2.0)
scikit-learn (version 0.21.3) scipy (version 1.2.0)
slurm (version 19.05.0) torchvision (version 0.4.0)
pytorch-lightning (version 0.10.0)

Custom Utilities

utils.py
models.py

Generate Data Partitions

makePartitionsUKBB.py
makePartitionsADNI.py

Dimension Reduction for Standard Machine Learning Methods

JSA_DR.sh
DR.py
JSA_DR_ADNI.sh
DR_ADNI.py

Standard Machine Learning Classifiers

JSA_SML.sh
run_SML.py

Standard Machine Learning Regressors

JSA_SML_reg.sh
run_SML_reg.py

Deep Learning Classifiers

JSA_DL.sh
run_DL.sh
run_DL.py

Deep Learning Regressors

JSA_DL_reg.sh
run_DL_reg.sh
run_DL_reg.py

Deep Learning Embeddings Visualization

tsneProjections.py

Deep Learning Saliency

JSA_DL_saliency.sh
run_DL_saliency.sh
run_DL_saliency.py

Comparative Analysis

Peng et al. model/pipeline used in Schulz et al.
JSA_run_train.sh
run_train.sh