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This paper is in the following e-collection/theme issue:

Patient Education for Cancer (332) Quality/Credibility of eHealth Information and Trust Issues (956) Innovations and Technology in Cancer Care (705) Information Seeking, Information Needs (660) Machine Learning (3303) Formative Evaluation of Digital Health Interventions (5320) Chatbots and Conversational Agents (1212) Generative Language Models Including ChatGPT (1601)

Published on in Vol 11 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/70176, first published .
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Reducing Hallucinations and Trade-Offs in Responses in Generative AI Chatbots for Cancer Information: Development and Evaluation Study

Reducing Hallucinations and Trade-Offs in Responses in Generative AI Chatbots for Cancer Information: Development and Evaluation Study

Authors of this article:

Sota Nishisako1 Author Orcid Image ;   Takahiro Higashi1, 2 Author Orcid Image ;   Fumihiko Wakao3 Author Orcid Image
Article Authors Cited by (23) Tweetations Metrics

Journals

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Books/Policy Documents

  1. Qadri S, Zahra S, Röning J, Lall B. Digital Health and Wireless Solutions: Integrating AI, LLMs and Multimodal Health Data for Next-Generation Decision Support. View
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Conference Proceedings

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  2. Khan T, Onwuegbuchi O. 2026 ASEE Annual Conference & Exposition Proceedings. A review on reducing AI and machine learning induced hallucinations in LLM using agent-to-agent validation View