Published February 12, 2024
| Version v1
Computational notebook
Open
Empirical data drift detection experiments on real-world medical imaging data: Codebase
Description
Codebase for the publication: "Empirical data drift detection experiments on real-world medical imaging data"
Python scripts.
Requirements: requirements.txt
Usage Instructions
## Installation
bashpip install -r requirements.txt
## Usage
Run pre-processing notebooks:
1. process_tabular_data.ipynb
2. get_metadata_final.ipynb
3. reductor_autoencoder.ipynb
4. reductor_classifier.ipynb
5. get_ae_predictions.ipynb
Run experiments:bash./run_sens_exp_ae_4000.sh./run_sens_exp_ae_predictions_4000.sh./run_sens_exp_performance_4000.sh./run_sens_exp_ae_clf_sample_size.sh./run_covid_exp.sh
Generate plots with generate_plots.ipynb.
Files
generate_plots.ipynb
Files
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