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Evaluating the efficacy of large language models in cardio-oncology patient education: a comparative analysis of accuracy, readability, and prompt engineering strategies
0
Zitationen
7
Autoren
2026
Jahr
Abstract
Publicly available LLMs provide largely accurate responses to cardio-oncology questions, yet their utility is constrained by inconsistent comprehensiveness and sensitivity to prompt design. While simplifying language improves readability, it risks compromising clinical relevance. Tailored fine-tuning and specialized evaluation frameworks are essential to optimize LLMs for patient education in cardio-oncology.
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