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

Patient Education for Cancer (327) Quality/Credibility of eHealth Information and Trust Issues (939) Innovations and Technology in Cancer Care (679) Information Seeking, Information Needs (651) Machine Learning (3147) Formative Evaluation of Digital Health Interventions (5104) Chatbots and Conversational Agents (1165) Generative Language Models Including ChatGPT (1501)

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 (17) Tweetations Metrics

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  1. Roca P, Zangri R, Rodriguez-Fernandez G, Sanchez-Pedreño M, García del Valle E. Artificial intelligence in the psychologist’s toolkit: Psypilot as a case study. Frontiers in Psychology 2026;17 View
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  13. Monika W, Dewi D, Nasution A, Onan A, Murakami Y. Retrieval-Augmented Generation for Curated Thematic Corpora: A Critical Survey, Bibliometric Evidence, and the ThemePath-RAG Framework. Information 2026;17(7):660 View
  14. Reynolds P, Pearl E. Reporting and transparency in laboratory animal science: Past achievements, present concerns and future directions. Laboratory Animals 2026 View
  15. Bernstein E, Bol B, Shanaa J, Ramsamooj A, Baldini T, Lum Z. Evaluating the Citation Accuracy of ChatGPT-5 Using the American Academy of Orthopaedic Surgeons Clinical Practice Guidelines. Cureus 2026 View

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

Conference Proceedings

  1. Kim Y, Kim M, Kim S, Cho S, Kim J. Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems. Design and Multi-level Evaluation of MAP-X: a Medically Aligned, Patient-Centered AI Explanation System View