Summary of Ulcergpt: a Multimodal Approach Leveraging Large Language and Vision Models For Diabetic Foot Ulcer Image Transcription, by Reza Basiri et al.
UlcerGPT: A Multimodal Approach Leveraging Large Language and Vision Models for Diabetic Foot Ulcer Image Transcription
by Reza Basiri, Ali Abedi, Chau Nguyen, Milos R. Popovic, Shehroz S. Khan
First submitted to arxiv on: 2 Oct 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| 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 proposed paper introduces UlcerGPT, a novel multimodal approach that leverages large language and vision models to transcribe diabetic foot ulcer (DFU) images. This framework combines the Large Language and Vision Assistant and Chat Generative Pre-trained Transformer models to detect, classify, and localize regions of interest in DFU images. The paper presents detailed experiments on a public dataset, evaluated by expert clinicians, which demonstrate promising results in the accuracy and efficiency of DFU transcription. This technology has potential applications in delivering timely care via telemedicine, particularly for patients with limited access to specialized services. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary UlcerGPT is a new way to use artificial intelligence to look at pictures of diabetic foot ulcers. These ulcers can cause serious problems if they’re not treated right away. Doctors usually need to see the ulcers in person, but that’s not always easy for patients who live far away. UlcerGPT uses special computer models to look at pictures of ulcers and figure out what’s going on. This can help doctors make a diagnosis sooner and start treatment faster. The people who made UlcerGPT tested it with real pictures and got good results. |
Keywords
» Artificial intelligence » Transformer
