---
base_model:
- meta-llama/Llama-3.2-1B-Instruct
license: mit
library_name: transformers
pipeline_tag: text-generation
tags:
- medical
- clinical-nlp
- information-extraction
- cardiology
- cmr
---

# CMR-EXTR: Structured Extraction from Cardiac MRI Reports

CMR-EXTR is a lightweight framework for converting free-text cardiac magnetic resonance (CMR) reports into structured, auditable data with per-field confidence estimation. It was introduced in the paper [Uncertainty-Aware Structured Data Extraction from Full CMR Reports via Distilled LLMs](https://huggingface.co/papers/2605.08045).

## Overview

The model is designed to support cohort assembly, longitudinal data curation, and clinical decision support in real-world clinical workflows. It performs structured information extraction from reports and assigns confidence scores to each extracted field, enabling efficient human review and quality control.

---

## Key Features

- **Structured Extraction**: Converts free-text CMR reports into predefined structured fields  
- **Per-field Confidence**: Provides uncertainty estimates for each extracted variable  
- **Offline Inference**: Fully deployable without external API dependencies  
- **Efficient Design**: Lightweight student model distilled from a larger teacher model  

---

## Code

The official implementation is available on GitHub:  
[CMR-EXTR](https://github.com/yuyi1005/CMR-EXTR)

---

## Method Summary

CMR-EXTR is built on a teacher–student distillation framework:

- A large teacher model generates high-quality structured outputs  
- A compact student model (based on Llama-3.2-1B) is trained to replicate these outputs efficiently  
- The student model supports fast and fully offline inference  

Uncertainty estimation integrates three complementary principles:

1. **Distribution Plausibility** — evaluates whether predictions follow expected value ranges  
2. **Sampling Stability** — measures consistency under stochastic decoding  
3. **Cross-field Consistency** — enforces logical relationships across extracted variables

---

## Citation

If you use this work, please cite:

```bibtex
@inproceedings{yu2026uncertainty,
  title={Uncertainty-Aware Structured Data Extraction from Full CMR Reports via Distilled LLMs},
  author={Yu, Yi and Martin, Parker and Bu, Zhenyu and Liu, Yixuan and Zheng, Yi-Yu and Simonetti, Orlando and Han, Yuchi and Xue, Yuan},
  booktitle={IEEE 23rd International Symposium on Biomedical Imaging (ISBI)},
  year={2026},
}
```