MedSparseFL: Sparse and Privacy-Preserving Federated Learning for Healthcare Applications
Abstract
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 filesLabels used in classification tasksTrain/Validation/Test splits for experiment reproducibility
Fields of Study & Subjects
Privacy-Preserving Technologies in Data
Artificial Intelligence in Healthcare and Education
Domain Adaptation and Few-Shot Learning
Publication details
- Journal / source
- Figshare
- Publication date
- 1 January 2026
- Language
- EN
- Document type
- Dataset