Update README.md

README.md

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-Educational XGBoost classifier predicting synthetic EF < 40% from engineered ECG/clinical features.
-Trained and tested only on synthetic data; current AUROC is ~0.895.
-Used to demonstrate the Team 4 MLOps pipeline, model registry, traceability, and evaluation workflow.
-Not for clinical diagnosis, treatment, screening, or validation.
+---
+
+library_name: xgboost
+pipeline_tag: tabular-classification
+tags: [xgboost, ecg, heart-failure, hfrEF, synthetic-data, mlops]
+license: other
+--------------
+
+# ECG Heart Failure XGBoost
+
+**Educational XGBoost classifier** predicting synthetic **EF < 40%** from engineered ECG and clinical features.
+
+* **Data:** Synthetic only
+* **AUROC:** ~0.895
+* **Purpose:** Team 4 MLOps, registry, traceability and evaluation
+* **Clinical use:** **Not for clinical diagnosis or decision-making**