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

Innovations and Technology in Cancer Care (490) Registered Report (714) Patient Education for Cancer (202) Generative Language Models Including ChatGPT (592) Cancer Survivorship (303) Vulnerable Populations in Health Research (163) Equity Issues in Information Distribution (27) Equity and Digital Divide (309) Artificial Intelligence, Machine Learning, and Natural Language Processing for Public Health (72)

Published on in Vol 11 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/67914, first published .
Evaluation of Large Language Models in Tailoring Educational Content for Cancer Survivors and Their Caregivers: Quality Analysis

Evaluation of Large Language Models in Tailoring Educational Content for Cancer Survivors and Their Caregivers: Quality Analysis

Evaluation of Large Language Models in Tailoring Educational Content for Cancer Survivors and Their Caregivers: Quality Analysis

Authors of this article:

Darren Liu1, 2 Author Orcid Image ;   Xiao Hu1, 2 Author Orcid Image ;   Canhua Xiao1, 3 Author Orcid Image ;   Jinbing Bai1, 3 Author Orcid Image ;   Zahra A Barandouzi1, 3 Author Orcid Image ;   Stephanie Lee1 Author Orcid Image ;   Caitlin Webster1 Author Orcid Image ;   La-Urshalar Brock1, 3 Author Orcid Image ;   Lindsay Lee4 Author Orcid Image ;   Delgersuren Bold1, 2 Author Orcid Image ;   Yufen Lin1, 3 Author Orcid Image
Article Authors Cited by (1) Tweetations Metrics

Journals

  1. Liu D, Lin Y, Yan R, Wang Z, Bold D, Hu X. Leveraging Artificial Intelligence for Digital Symptom Management in Oncology: The Development of CRCWeb. JMIR Cancer 2025;11:e68516 View