Summary of Assessing the Potential Of Mid-sized Language Models For Clinical Qa, by Elliot Bolton et al.
Assessing The Potential Of Mid-Sized Language Models For Clinical QA
by Elliot Bolton, Betty Xiong, Vijaytha Muralidharan, Joel Schamroth, Vivek Muralidharan, Christopher D. Manning, Roxana Daneshjou
First submitted to arxiv on: 24 Apr 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 Large language models like GPT-4 and Med-PaLM excel in clinical tasks, but they require significant compute resources, are proprietary, and cannot be deployed directly. Mid-size models like BioGPT-large, BioMedLM, LLaMA 2, and Mistral 7B address these limitations, but their suitability for clinical applications remains understudied. This study compares the performance of these mid-sized models on two clinical question-answering tasks: MedQA and consumer query answering. The results show that Mistral 7B outperforms other models, achieving a MedQA score of 63.0%, approaching the original Med-PaLM’s performance. While Mistral 7B produces plausible responses for consumer health queries, there is still room for improvement. This study provides the first comprehensive assessment of open-source mid-sized models on clinical tasks. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This research compares different types of language models to see which one works best for medical and healthcare questions. These models are like super smart computers that can understand and answer questions. The researchers looked at two kinds of questions: ones that need special medical knowledge, and everyday consumer health queries. They found that one model called Mistral 7B performed the best on both types of questions. While it’s not perfect yet, it’s a step forward in using technology to help with healthcare. |
Keywords
* Artificial intelligence * Gpt * Llama * Palm * Question answering
