Update README.md

README.md

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-license: cc-by-nc-4.0
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+---
+license: cc-by-nc-4.0
+---
+# CaseReportBench: Clinical Dense Extraction Benchmark
+
+**CaseReportBench** is a curated benchmark dataset designed to evaluate the ability of large language models to perform **dense information extraction** from **clinical case reports**, particularly in the context of **rare disease diagnosis**.
+
+This dataset supports fine-grained, system-wise phenotype extraction and structured diagnostic reasoning evaluation.
+
+---
+
+## Key Features
+
+- Expert-annotated dense labels simulating comprehensive head-to-toe clinical assessments, capturing multi-system findings as encountered in real-world diagnostic reasoning
+- Domain: Clinical Case Reports (PubmedCentral indexed)
+- Use case: Medical IE, LLM evaluation, Rare disease diagnosis
+- Data type: JSON with structured system-wise output
+- Evaluation metrics: Token Selection Rate, Levenshtein Similarity, Exact Match
+
+---
+
+## Dataset Structure
+
+Each record includes:
+
+- `id`: Unique document identifier
+- `text`: Raw case report
+- `extracted_labels`: Dense structured annotations by system (e.g., nervous system, metabolic)
+- `diagnosis`: Gold standard diagnosis
+- `source`: PubMed ID or citation
+
+---
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("cxyzhang/caseReportBench_ClinicalDenseExtraction_Benchmark")
+print(ds["train"][0])