Summary of Kargen: Knowledge-enhanced Automated Radiology Report Generation Using Large Language Models, by Yingshu Li et al.
KARGEN: Knowledge-enhanced Automated Radiology Report Generation Using Large Language Models
by Yingshu Li, Zhanyu Wang, Yunyi Liu, Lei Wang, Lingqiao Liu, Luping Zhou
First submitted to arxiv on: 9 Sep 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This study leverages Large Language Models (LLMs) for narrative generation, logical reasoning, and common-sense knowledge integration to enhance automated radiology report generation (R2Gen). The researchers propose KARGEN, a Knowledge-enhanced Automated radiology Report GENeration framework based on LLMs. By integrating a knowledge graph, the framework unlocks chest disease-related knowledge within the LLM to improve the clinical utility of generated reports. Two fusion methods are explored to automatically prioritize and select relevant features from regional image features and graph-enhanced disease-related features. The fused features are then employed by LLM to generate reports that are more sensitive to diseases and of improved quality. Promising results are demonstrated on the MIMIC-CXR and IU-Xray datasets. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This research uses powerful language models to help create better medical reports for X-rays. These models can understand and generate text, but they need guidance to focus on specific information. The researchers created a new way to use these models, called KARGEN, which adds more knowledge to the model to make it better at generating reports. This approach helps doctors by giving them more accurate and detailed reports about what’s shown in X-rays. The results look promising, with good performance on two different datasets. |
Keywords
» Artificial intelligence » Knowledge graph
