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alzheimers_nn
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Nicholas Schense fb995072b3 continuing work on rewrite 4 dagar sedan
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utils fb995072b3 continuing work on rewrite 4 dagar sedan
.gitignore a02334abbf More work done on overall stats - not sure why so many files changed 10 månader sedan
README.md 72c64b23d9 Update 'README.md' 4 månader sedan
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calibration_xarray.py 4549b2b349 Worked on calibration (little success) and began tweaking graphs for presentation and poster 9 månader sedan
config.toml 53c6d721b1 Beginning work on rewrite 1 vecka sedan
dataset_size.py 26e4e9c3f3 Commit of work from summer 1 månad sedan
ensemble_predict.py fb995072b3 continuing work on rewrite 4 dagar sedan
model_evaluation.py fb995072b3 continuing work on rewrite 4 dagar sedan
sensitivity_analysis.py fb995072b3 continuing work on rewrite 4 dagar sedan
threshold.py 53c6d721b1 Beginning work on rewrite 1 vecka sedan
threshold_refac.py fb995072b3 continuing work on rewrite 4 dagar sedan
threshold_xarray.py fb995072b3 continuing work on rewrite 4 dagar sedan
train_cnn.py a02334abbf More work done on overall stats - not sure why so many files changed 10 månader sedan
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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_xarray.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. The other two threshold files are old implementations. 'sensitivity_analysis.py' can be optionally used to generate some model number sensitivity data, but the implementation is buggy currently. Apologies for the messy code throughout!