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FL-CheX: Federated Learning Benchmark for Chest Disease Classification
Author: Md. Sajjad Ullah
Affiliation: CSE, University of Asia Pacific, Bangladesh
Date: March 2026
Dataset Summary
FL-CheX is the first federated learning benchmark combining demographic, Non-IID, and scanner heterogeneity for chest disease classification research.
15 pre-partitioned FL client nodes built from CheXpert (Stanford) with real DenseNet-121 features.
Load Dataset
from datasets import load_dataset
ds = load_dataset("mdsajjadullah/fl-chex-benchmark")
Dataset Structure
- 5 Demographic nodes (age × gender)
- 5 Non-IID Hospital nodes (disease-specialized)
- 5 Scanner nodes (hardware quality variation)
Citation
@misc{flchex2026,
author = {Md. Sajjad Ullah},
title = {FL-CheX: A Federated Learning Benchmark},
year = {2026}
}
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