68 lines
2.4 KiB
Markdown
68 lines
2.4 KiB
Markdown
---
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base_model:
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- meta-llama/Llama-3.2-1B-Instruct
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license: mit
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library_name: transformers
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pipeline_tag: text-generation
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tags:
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- medical
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- clinical-nlp
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- information-extraction
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- cardiology
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- cmr
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---
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# CMR-EXTR: Structured Extraction from Cardiac MRI Reports
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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).
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## Overview
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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.
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---
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## Key Features
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- **Structured Extraction**: Converts free-text CMR reports into predefined structured fields
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- **Per-field Confidence**: Provides uncertainty estimates for each extracted variable
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- **Offline Inference**: Fully deployable without external API dependencies
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- **Efficient Design**: Lightweight student model distilled from a larger teacher model
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---
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## Code
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The official implementation is available on GitHub:
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[CMR-EXTR](https://github.com/yuyi1005/CMR-EXTR)
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---
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## Method Summary
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CMR-EXTR is built on a teacher–student distillation framework:
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- A large teacher model generates high-quality structured outputs
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- A compact student model (based on Llama-3.2-1B) is trained to replicate these outputs efficiently
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- The student model supports fast and fully offline inference
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Uncertainty estimation integrates three complementary principles:
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1. **Distribution Plausibility** — evaluates whether predictions follow expected value ranges
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2. **Sampling Stability** — measures consistency under stochastic decoding
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3. **Cross-field Consistency** — enforces logical relationships across extracted variables
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---
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## Citation
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If you use this work, please cite:
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```bibtex
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@inproceedings{yu2026uncertainty,
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title={Uncertainty-Aware Structured Data Extraction from Full CMR Reports via Distilled LLMs},
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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},
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booktitle={IEEE 23rd International Symposium on Biomedical Imaging (ISBI)},
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year={2026},
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}
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``` |