Summary of Rexplain: Translating Radiology Into Patient-friendly Video Reports, by Luyang Luo et al.
ReXplain: Translating Radiology into Patient-Friendly Video Reports
by Luyang Luo, Jenanan Vairavamurthy, Xiaoman Zhang, Abhinav Kumar, Ramon R. Ter-Oganesyan, Stuart T. Schroff, Dan Shilo, Rydhwana Hossain, Mike Moritz, Pranav Rajpurkar
First submitted to arxiv on: 1 Oct 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Image and Video Processing (eess.IV)
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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 A novel AI-driven system called ReXplain translates radiology reports into patient-friendly video explanations, addressing the issue of incomprehensible reports that can lead to anxiety and poor health outcomes. By integrating large language models for text simplification, image segmentation, and avatar generation, ReXplain produces comprehensive explanations with plain language, highlighted imagery, and 3D organ renderings in video format. A proof-of-concept study involving radiologists suggests that ReXplain-generated explanations can accurately convey radiological information and simulate one-on-one consultations, potentially improving patient engagement and satisfaction in radiology care. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary A new system called ReXplain helps patients understand their medical reports by making them easy to understand. This system uses artificial intelligence to take complicated medical text and turn it into simple language, with pictures and videos that show the body parts being discussed. Doctors gave feedback on how well this system worked, and the results are promising. This could be a big step forward in helping patients feel more comfortable and informed about their medical care. |
Keywords
» Artificial intelligence » Image segmentation
