Update README.md

README.md

@@ -1,3 +1,54 @@
----
-license: cc-by-4.0
----
+---
+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}
+}
+```
+```