---
license: cc-by-4.0
task_categories:
  - tabular-classification
language:
  - en
tags:
  - federated-learning
  - medical
  - chest-xray
  - fairness
  - healthcare
  - benchmark
  - chexpert
  - densenet
pretty_name: FL-CheX Federated Learning Benchmark
size_categories:
  - 10K<n<100K
---

# 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
```python
from datasets import load_dataset
ds = load_dataset("YOUR_USERNAME/fl-chex-benchmark")
```

## Dataset Structure
- 5 Demographic nodes (age × gender)
- 5 Non-IID Hospital nodes (disease-specialized)
- 5 Scanner nodes (hardware quality variation)

## Citation
```bibtex
@misc{flchex2026,
  author = {Md. Sajjad Ullah},
  title  = {FL-CheX: A Federated Learning Benchmark},
  year   = {2026}
}
```
```