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The reliability and readability of large language models in answering patient questions on maintenance hemodialysis: A comparative study
0
Zitationen
6
Autoren
2026
Jahr
Abstract
Current large language models (LLMs) exhibit significant variability in delivering maintenance hemodialysis information. While all five evaluated models demonstrated limitations in information quality, transparency, and readability, Perplexity performed relatively better overall. However, persistent deficiencies in source attribution, language accessibility, and response consistency limit their immediate clinical and educational utility. Future LLM development should prioritize readability optimization and context-aware customization to better support patient education.
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