MedSparseFL: Sparse and Privacy-Preserving Federated Learning for Healthcare Applications

This project provides processed data indexes for reproducing experiments from the MedSparseFL study, a sparse and privacy-preserving federated learning framework for healthcare applications. The datasets include CheXpert and HAM10000. For each dataset, CSV files (chexpert_index.csv and ham10000_index.csv) contain: Image IDs referencing the official dataset files Labels used in classification tasks Train/Validation/Test splits for experiment reproducibility