A Comparative Analysis of AI Models in Complex Medical Decision-Making Scenarios: Evaluating ChatGPT, Claude AI, Bard, and Perplexity

被引:2
|
作者
Uppalapati, Vamsi Krishna [1 ]
Nag, Deb Sanjay [1 ]
机构
[1] Tata Main Hosp, Dept Anesthesiol, Jamshedpur, India
关键词
future medicine; ai efficacy; ai comparison; healthcare ai; medical decision-making;
D O I
10.7759/cureus.52485
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
This study rigorously evaluates the performance of four artificial intelligence (AI) language modelsChatGPT, Claude AI, Google Bard, and Perplexity AI - across four key metrics: accuracy, relevance, clarity, and completeness. We used a strong mix of research methods, getting opinions from 14 scenarios. This helped us make sure our findings were accurate and dependable. The study showed that Claude AI performs better than others because it gives complete responses. Its average score was 3.64 for relevance and 3.43 for completeness compared to other AI tools. ChatGPT always did well, and Google Bard had unclear responses, which varied greatly, making it difficult to understand it, so there was no consistency in Google Bard. These results give important information about what AI language models are doing well or not for medical suggestions. They help us use them better, telling us how to improve future tech changes that use AI. The study shows that AI abilities match complex medical scenarios.
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页数:6
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