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Empirical data drift detection experiments on real-world medical imaging data: Codebase

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 12 Feb 2024Publisher:Zenodo
Authors: Kore, Ali; Abbasi Bavil, Elyar; Subasri, Vallijah; Abdalla, Moustafa; Fine, Benjamin; Dolatabadi, Elham; Abdalla, Mohamed;

doi: 10.5281/zenodo.10652201

Empirical data drift detection experiments on real-world medical imaging data: Codebase

Abstract

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 ## UsageRun pre-processing notebooks:1. process_tabular_data.ipynb2. get_metadata_final.ipynb3. reductor_autoencoder.ipynb4. reductor_classifier.ipynb5. 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.

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