Article record

生成式人工智能模型回答鼻息肉常见患者问题的表现

Performance of Generative Artificial Intelligence Models in Answering Common Patient Questions About Nasal Polyps.

AI/ML鼻科IF 7.7Q1

文献信息

PMID	42950951
原文	在 PubMed 查看原文 ↗
发表日期	2026
作者	Hana B Ruran 查看其他 7 位作者 Sankalp Bhoyar；Saleh Alsulami；Anna Gray；Wanda Phipatanakul；Stella E Lee；Ahmad R Sedaghat；Thinh H Nguyen
作者单位	Case Western Reserve University School of Medicine, Cleveland, OH, USA. Electronic address: hana.ruran@case.edu. 查看其他 5 条单位信息 Boston University, Boston, MA, USA.；Division of Immunology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.；Department of Otolaryngology-Head and Neck Surgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.；Department of Otolaryngology - Head and Neck Surgery University of Cincinnati, College of Medicine, Cincinnati, OH, USA.；Division of Immunology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA. Electronic address: thinh.nguyen@childrens.harvard.edu.
期刊	The journal of allergy and clinical immunology. In practice
SCI 分区	Q1
IF	7.7
研究类型	AI/ML · 临床
所属专科	鼻科

中文摘要

生成式人工智能平台在回答常见鼻息肉问题时，在准确性、时效性、相关性和可理解性以及临床安全性方面存在差异。临床医生在为使用人工智能生成健康信息的患者提供咨询时，应认识到这些权衡。

英文摘要

Generative artificial intelligence platforms differed in accuracy, currency, relevance, and understandability, and clinical safety when answering common nasal-polyp questions. Clinicians should recognize these tradeoffs when counseling patients who use AI-generated health information.