---
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}
}
```