Update README.md

README.md

@@ -12,23 +12,31 @@ size_categories:
   - 10K<n<100K
 ---
 
-🏛️ Dataset Summary
+🏛️ **Dataset Summary**
 
-The Global Medical Institutions & Hierarchy Graph is a structured directory of 11,521 healthcare and research institutions spanning multiple countries. Crucially, it captures organizational hierarchy (ultimate_parent_id), making it an asset for healthcare knowledge graphs, entity resolution, and clinical trial site mapping.
+A global directory of medical institutions and organizations covering 14,065 entities. Provides basic organizational profiles with drug pipeline association counts.
 
-🚀 Key Features
+**🚀 Key Features**
 
-•
-Multi-Country Coverage: Institutions drawn from major countries, enabling cross-border healthcare network analysis.
+- **Global Coverage:** `country` field spans institutions worldwide.
+- **Drug Association Count:** `total_drug` indicates the number of drugs associated with each institution.
+- **Organization Size:** `employee_number` available for ~49% of records.
 
-•
-Hierarchical Mapping: ultimate_parent_id maps complex institutional networks (e.g., university hospitals to parent universities).
+**💻 Quick Start & MCP Integration**
 
-•
-Multilingual Support: Includes local display names (display_name) and English translations (name_en).
+```python
+from datasets import load_dataset
 
-•
-Search Optimized: Pre-computed search_score for integration into search engines and RAG pipelines.
+dataset = load_dataset("your-org/medical-institutions", split="train")
+print(dataset[0]["name"])
+# Output: 'Unlimited Bio'
+print(dataset[0]["country"])
+# Output: 'Honduras'
+print(dataset[0]["total_drug"])
+# Output: 1
+```
+
+---
 
 ## 🔗 Resources
 - **Developer Portal**: [open.patsnap.com](https://open.patsnap.com)