Summary of M4cxr: Exploring Multi-task Potentials Of Multi-modal Large Language Models For Chest X-ray Interpretation, by Jonggwon Park et al.
M4CXR: Exploring Multi-task Potentials of Multi-modal Large Language Models for Chest X-ray Interpretation
by Jonggwon Park, Soobum Kim, Byungmu Yoon, Jihun Hyun, Kyoyun Choi
First submitted to arxiv on: 29 Aug 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Computation and Language (cs.CL)
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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 The paper presents M4CXR, a multi-modal large language model designed to enhance chest X-ray interpretation. The model is trained on a visual instruction-following dataset that integrates various task-specific datasets in a conversational format. It supports multiple tasks such as medical report generation (MRG), visual grounding, and visual question answering (VQA). M4CXR achieves state-of-the-art clinical accuracy in MRG by employing a chain-of-thought prompting strategy. The model is adaptable to various MRG scenarios depending on the available inputs. In addition to MRG, it performs visual grounding at a level comparable to specialized models and demonstrates outstanding performance in VQA. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary M4CXR is a new AI tool that helps doctors read X-ray images more accurately. It’s like a super-smart language model that can understand what it sees in an X-ray picture and write a report about what it finds. The report is accurate because the AI was trained on lots of examples and can even generate reports based on single or multiple X-ray images. This tool also helps with other tasks, like answering questions about what’s shown in the X-ray picture. Overall, M4CXR is a really useful tool that can help doctors make better diagnoses. |
Keywords
» Artificial intelligence » Grounding » Language model » Large language model » Multi modal » Prompting » Question answering
