Accueil Explorer Aide
Connexion
nschense
/
alzheimers_nn
1
0
Fork 0
Fichiers Tickets 0 Pull Requests 0 Wiki

Aucune description

Aborescence: 300dc9dcf4
Branches Tags
alzheimers_nn
ZIP TAR.GZ
nschense 300dc9dcf4 Update 'config.toml' in preparation for sharing il y a 7 mois
.vscode a02334abbf More work done on overall stats - not sure why so many files changed il y a 1 an
utils a02334abbf More work done on overall stats - not sure why so many files changed il y a 1 an
.gitignore a02334abbf More work done on overall stats - not sure why so many files changed il y a 1 an
LP_ADNIMERGE.csv a02334abbf More work done on overall stats - not sure why so many files changed il y a 1 an
README.md c48455a8d7 Update 'README.md' in preparation for sharing il y a 7 mois
bayesian.py a02334abbf More work done on overall stats - not sure why so many files changed il y a 1 an
config.toml 300dc9dcf4 Update 'config.toml' in preparation for sharing il y a 7 mois
daily_log.md a02334abbf More work done on overall stats - not sure why so many files changed il y a 1 an
ensemble_predict.py a02334abbf More work done on overall stats - not sure why so many files changed il y a 1 an
planning.md a02334abbf More work done on overall stats - not sure why so many files changed il y a 1 an
ruff.toml a02334abbf More work done on overall stats - not sure why so many files changed il y a 1 an
sensitivity_analysis.py a02334abbf More work done on overall stats - not sure why so many files changed il y a 1 an
threshold.py 1083b2301b Completed refactor to xarray - working on minimial calibration and sensitivity analysis il y a 1 an
threshold_refac.py 1083b2301b Completed refactor to xarray - working on minimial calibration and sensitivity analysis il y a 1 an
threshold_xarray.py 1083b2301b Completed refactor to xarray - working on minimial calibration and sensitivity analysis il y a 1 an
train_cnn.py a02334abbf More work done on overall stats - not sure why so many files changed il y a 1 an

README.md

Alzheimers Diagnosis Neural Net Project Rewrite

This code is the current version for the Alzheimers CNN uncertanity estimation project. The project consists of a set of main scripts (in the root folder) and some utilities. In order to use the project:

  1. Edit "config.toml" with the details of the ensemble that you would like to train (size, name, epochs etc). Make sure that the model name and ensemble name are the same if you'd like to run the ensemble analysis later.
  2. Run "train_cnn.py". This will train and save a new ensemble of CNN models using the name and congfiguration options given in the config file.
  3. Run "ensemble_predict.py". This will generate the predictions of the models on the test and validation datasets and save them to the model ensemble folder.
  4. Run "threshold.py". This run some analysis on the ensemble and generates a set of graphs and statistics.

"bayesian.py" is unfinished and does not currently work.