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Background <p>Artificial intelligence AI platforms, such as Gemini, ChatGPT, DeepSeek, and Perplexity, are increasingly utilized to support clinical decision-making, yet their accuracy in specific medical domains remains variable. This study assessed the performance of these AI chatbots in responding to clinical questions commonly posed by surgeons in the context of salivary gland cancer, a field closely related to oral and maxillofacial oncology.</p> Methods <p>Thirty clinical questions related to salivary gland malignancies were created according to the ASCO 2021 guidelines. Two researchers posted on four AI chatbot platforms: ChatGPT-4o, DeepSeek, Gemini, and Peperlixity. These questions were queried three times daily over ten days, yielding a total of 2700 responses that were coded as correct or incorrect. The accuracy of each response was statistically analyzed, and overall accuracy rates for each AI platform were calculated.</p> Results <p>DeepSeek achieved the highest accuracy rate at 86.9%, followed by Gemini at 78.9%, ChatGPT-4o at 72.8%, and Perplexity at 71.6%.</p> Conclusion <p>Despite demonstrating substantial potential, current AI chatbots have not yet achieved sufficient accuracy for standalone clinical use in salivary gland cancer in clinical applications. Enhancements in AI capabilities and rigorous clinical validation are necessary to ensure patient safety and effectiveness in clinical practice.</p>

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Evaluation of deepseek, gemini, ChatGPT-4o, and perplexity in responding to salivary gland cancer

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年8月23日

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  • Ahmed Bashah,
  • Abdulkhaleq Salem,
  • Ali Al-waqeerah,
  • Eslam Ghaleb,
  • Natheer Wahan,
  • Ahmed Awad,
  • Omran Al-tos,
  • Gang Chen

摘要

Background

Artificial intelligence AI platforms, such as Gemini, ChatGPT, DeepSeek, and Perplexity, are increasingly utilized to support clinical decision-making, yet their accuracy in specific medical domains remains variable. This study assessed the performance of these AI chatbots in responding to clinical questions commonly posed by surgeons in the context of salivary gland cancer, a field closely related to oral and maxillofacial oncology.

Methods

Thirty clinical questions related to salivary gland malignancies were created according to the ASCO 2021 guidelines. Two researchers posted on four AI chatbot platforms: ChatGPT-4o, DeepSeek, Gemini, and Peperlixity. These questions were queried three times daily over ten days, yielding a total of 2700 responses that were coded as correct or incorrect. The accuracy of each response was statistically analyzed, and overall accuracy rates for each AI platform were calculated.

Results

DeepSeek achieved the highest accuracy rate at 86.9%, followed by Gemini at 78.9%, ChatGPT-4o at 72.8%, and Perplexity at 71.6%.

Conclusion

Despite demonstrating substantial potential, current AI chatbots have not yet achieved sufficient accuracy for standalone clinical use in salivary gland cancer in clinical applications. Enhancements in AI capabilities and rigorous clinical validation are necessary to ensure patient safety and effectiveness in clinical practice.