Add dataset card with paper link, GitHub link, and benchmark info

README.md

@@ -1,3 +1,57 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+task_categories:
+- text-generation
+language:
+- en
+tags:
+- medical
+- clinical
+- EHR
+---
+
+# AGENTEHR: Advancing Autonomous Clinical Decision-Making via Retrospective Summarization
+
+[**Paper**](https://huggingface.co/papers/2601.13918) | [**Code**](https://github.com/BlueZeros/AgentEHR)
+
+**AGENTEHR** is a novel benchmark designed to bridge the gap between idealized experimental settings and realistic clinical environments. Unlike previous tasks that focus on factual retrieval, AGENTEHR challenges agents to perform complex **clinical decision-making**—such as diagnosis and treatment planning—directly within raw, high-noise EHR databases.
+
+## 💡 Key Features
+* **Realistic Clinical Benchmark**: Covers six core tasks (Diagnoses, Labevents, Microbiology, Prescriptions, Procedures, and Transfers) spanning the entire patient hospitalization lifecycle.
+* **Toolbox MCP Server**: A standardized interface providing agents access to over **19 specialized tools**, including SQL execution, temporal filtering, and semantic search.
+* **Retrospective Reasoning**: Supports the evaluation of frameworks that re-evaluate interaction history to capture latent correlations and ensure logical coherence.
+* **Experience Memory Bank**: Facilitates strategies that crystallize successful approaches into an external memory bank.
+
+## 📊 Benchmark Structure
+AGENTEHR is organized into three experimental subsets based on MIMIC-IV and MIMIC-III to evaluate generalization and robustness:
+
+| Subset | Distribution Type | Description |
+| :--- | :--- | :--- |
+| **MIMIC-IV-Common** | In-Distribution | Primary benchmark assessing standard clinical reasoning capabilities on prevalent conditions. |
+| **MIMIC-IV-Rare** | Label-Shift OOD | Evaluates the agent's ability to handle low-prevalence diseases where parametric knowledge is weaker. |
+| **MIMIC-III** | Systemic-Shift OOD | Presents fundamental differences in table schema and higher recording density/noise. |
+
+## ⚡ Quick Start
+
+### Environment Setup
+To use this benchmark with the official code, follow these steps:
+```bash
+git clone https://github.com/BlueZeros/AgentEHR.git
+cd AgentEHR
+pip install -r requirements.txt
+pip install -U vllm
+```
+
+### Database Preparation
+Download the dataset from this repository. Copy the `EHRAgentBench` and `MIMICIIIAgentBench` folders into the `./data` folder in your root directory of the cloned repository.
+
+## Citation
+If you find our work helpful, please cite our paper:
+```bibtex
+@article{liao2026agentehr,
+  title={AgentEHR: Advancing Autonomous Clinical Decision-Making via Retrospective Summarization},
+  author={Yusheng Liao and Chuan Xuan and Yutong Cai and Lina Yang and Zhe Chen and Yanfeng Wang and Yu Wang},
+  journal={arXiv preprint arXiv:2601.13918},
+  year={2026}
+}
+```