AI Chatbot for Cancer Patient Support: Development and Evaluation Using Llama 3.1, Mistral 7B, and PHI 3B

This study develops and evaluates a question-answering (Q&A) system for breast cancer patients using generative AI technologies. We compared the performance of three language models-Llama 3.1, Mistral 7B and Phi 3.5. The goal is to integrate this system into a patient-facing application, providing personalised, interactive support based on reliable sources such as Cancer Research UK. However, findings indicate that misinformation remains a significant concern. Medical chatbots utilising retrieval augmented generation (RAG) providing clinical information require significant refinement before being suitable for clinical use.

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Publication Details

Journal
Studies in health technology and informatics
Published
2025-05-15
DOI
https://doi.org/10.3233/shti250494
Citations
3
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
11.68
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article

AI Chatbot for Cancer Patient Support: Development and Evaluation Using Llama 3.1, Mistral 7B, and PHI 3B

R. Lee, Franz Gruber, Arlene Casey, Matúš Falis et al.
3 citations
Studies in health technology and informatics
Artificial Intelligence in Healthcare and Education
11.68
article

AI Chatbot for Cancer Patient Support: Development and Evaluation Using Llama 3.1, Mistral 7B, and PHI 3B

R. Lee, Franz Gruber, Arlene Casey, Matúš Falis, T. Nash, Samuel McInerney
article en
3 citations

Abstract

This study develops and evaluates a question-answering (Q&A) system for breast cancer patients using generative AI technologies. We compared the performance of three language models-Llama 3.1, Mistral 7B and Phi 3.5. The goal is to integrate this system into a patient-facing application, providing personalised, interactive support based on reliable sources such as Cancer Research UK. However, findings indicate that misinformation remains a significant concern. Medical chatbots utilising retrieval augmented generation (RAG) providing clinical information require significant refinement before being suitable for clinical use.

Studies in health technology and informaticsVol. 327
NHS Greater Glasgow and Clyde (GB), University of Edinburgh (GB)
Openalex Percentile: Top 2%
Artificial Intelligence in Healthcare and Education
11.68
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