Responses of Large Language Models to Frequently Asked Questions in Breast Imaging

What is it about?

Large language models (LLMs) like ChatGPT-4, Gemini, and Microsoft Copilot have transformed AI by generating human-like text and answering queries accurately. This study evaluates the readability and accuracy of LLM responses to frequently asked questions in breast imaging, a field critical for early disease detection. The findings reveal significant differences among LLMs: Gemini and Microsoft Copilot produced more readable responses, while ChatGPT-4 provided more accurate answers.

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Photo by Angiola Harry on Unsplash

Photo by Angiola Harry on Unsplash

Why is it important?

These insights are crucial for enhancing patient health literacy and engagement. The study underscores the potential of LLMs in healthcare, highlighting the need for ongoing evaluation to ensure quality and consistency. Future research should focus on the longitudinal impact of LLM interactions on patient outcomes and the continuous improvement of AI tools in medical communication. This work contributes to the evolving role of AI in healthcare, aiming to improve patient education and support informed decision-making.