Summary of Semiollm: Assessing Large Language Models For Semiological Analysis in Epilepsy Research, by Meghal Dani et al.
SemioLLM: Assessing Large Language Models for Semiological Analysis in Epilepsy Research
by Meghal Dani, Muthu Jeyanthi Prakash, Zeynep Akata, Stefanie Liebe
First submitted to arxiv on: 3 Jul 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 A study evaluates large language models (LLMs) on their ability to diagnose epilepsy based on patient medical histories. Researchers tested four state-of-the-art LLMs (GPT-3.5, GPT-4, Mixtral 8x7B, and Qwen-72chat) using an annotated clinical database containing 1269 entries. They assessed the models’ performance, confidence, reasoning, and citation abilities compared to clinical evaluations. The results show that with prompt engineering, some models achieved close-to-clinical performance and reasoning, but also exhibited pitfalls like overconfidence, poor performance, and hallucinations. This study provides a benchmark for evaluating LLMs in medical diagnosis and highlights their potential to aid diagnostic processes. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Large language models are really smart computers that can understand human language. In this study, scientists tested these models on how well they could diagnose epilepsy from patient medical records. They used a special database with 1269 entries to see which model was best at making diagnoses. The results showed that some models were very good and even got close to the level of human doctors! However, not all models did as well, and some made mistakes like being too confident or making things up. This study helps us understand how these super smart computers can be used in medicine. |
Keywords
* Artificial intelligence * Gpt * Prompt
