A preliminary review of the utility of artificial intelligence to detect eosinophilic chronic rhinosinusitis.

IF 7.2 2区医学 Q1 OTORHINOLARYNGOLOGY

International Forum of Allergy & Rhinology Pub Date : 2024-10-10 DOI:10.1002/alr.23463

Jayanth Rajan, Ross Rosen, Daniel Karasik, John Richter, Claudia Cabrera, Brian D'Anza, Kenneth Rodriguez, Sanjeet V Rangarajan

引用次数: 0

Abstract

Key points: While typically diagnosed with biopsy, ECRS may be predicted preoperatively with the use of AI. Various AI models have been used, with pooled sensitivity of 0.857 and specificity of 0.850. We found no statistically significant difference between the accuracy of various AI models.

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人工智能在检测嗜酸性粒细胞慢性鼻炎方面的实用性初步评述。

要点：虽然 ECRS 通常是通过活组织检查诊断出来的，但也可以通过 AI 进行术前预测。我们使用了各种人工智能模型，汇总灵敏度为 0.857，特异度为 0.850。我们发现各种人工智能模型的准确性在统计学上没有明显差异。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Forum of Allergy & Rhinology OTORHINOLARYNGOLOGY-

CiteScore

11.70

自引率

10.90%

发文量

185

审稿时长

6-12 weeks

期刊介绍： International Forum of Allergy & Rhinologyis a peer-reviewed scientific journal, and the Official Journal of the American Rhinologic Society and the American Academy of Otolaryngic Allergy. International Forum of Allergy Rhinology provides a forum for clinical researchers, basic scientists, clinicians, and others to publish original research and explore controversies in the medical and surgical treatment of patients with otolaryngic allergy, rhinologic, and skull base conditions. The application of current research to the management of otolaryngic allergy, rhinologic, and skull base diseases and the need for further investigation will be highlighted.