Summary of Eyegpt: Ophthalmic Assistant with Large Language Models, by Xiaolan Chen et al.
EyeGPT: Ophthalmic Assistant with Large Language Models
by Xiaolan Chen, Ziwei Zhao, Weiyi Zhang, Pusheng Xu, Le Gao, Mingpu Xu, Yue Wu, Yinwen Li, Danli Shi, Mingguang He
First submitted to arxiv on: 29 Feb 2024
Categories
- Main: Computation and Language (cs.CL)
- 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 The proposed EyeGPT model is a specialized large language model designed specifically for ophthalmology, utilizing three optimization strategies: role-playing, finetuning, and retrieval-augmented generation. The model was evaluated using a comprehensive framework that included a diverse dataset covering various subspecialties of ophthalmology, different users, and diverse inquiry intents. Performance metrics included accuracy, understandability, trustworthiness, empathy, and the proportion of hallucinations. The most effective variant exhibited comparable levels of understandability, trustworthiness, and empathy to human ophthalmologists. This study provides valuable insights for future research, enabling comprehensive comparisons and evaluations of different strategies for developing specialized LLMs in ophthalmology. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary EyeGPT is a new AI model that helps doctors with eye problems. It’s like a super smart assistant that can understand and respond to questions about eye care. The researchers created EyeGPT by teaching it how to talk like an expert eye doctor. They tested it using lots of different scenarios and asked it questions to see if it could answer them correctly. The results showed that EyeGPT was just as good as a real eye doctor at understanding and responding to patient questions. |
Keywords
» Artificial intelligence » Large language model » Optimization » Retrieval augmented generation
