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Using Natural Language Processing to Explore Patient Perspectives on AI Avatars in Support Materials for Patients With Breast Cancer: Survey Study

Using Natural Language Processing to Explore Patient Perspectives on AI Avatars in Support Materials for Patients With Breast Cancer: Survey Study

Within the health care domain, LLM summarization techniques have predominantly been explored in the context of electronic health records and clinical notes summarization [42,43]; for example, Tariq et al [44] used the text-to-text transfer transformer (T5) model to generate layperson-friendly summaries of clinical radiology notes, while Van Veen et al [45] evaluated various LLMs across a range of clinical text summarization tasks and found that fine-tuned language net–T5 (FLAN-T5) and GPT-4 performed best overall

Eleanor Cheese, Raouef Ahmed Bichoo, Kartikae Grover, Dorin Dumitru, Alexandros Zenonos, Joanne Groark, Douglas Gibson, Rebecca Pope

J Med Internet Res 2025;27:e70971

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