人工智能检测嗜酸性粒细胞性慢性鼻-鼻窦炎效用的初步综述
A preliminary review of the utility of artificial intelligence to detect eosinophilic chronic rhinosinusitis.
作者信息
Rajan Jayanth, Rosen Ross, Karasik Daniel, Richter John, Cabrera Claudia, D'Anza Brian, Rodriguez Kenneth, Rangarajan Sanjeet V
机构信息
Department of Surgery, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA.
Case Western Reserve University School of Medicine, Cleveland, Ohio, USA.
出版信息
Int Forum Allergy Rhinol. 2025 Feb;15(2):203-207. doi: 10.1002/alr.23463. Epub 2024 Oct 10.
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.
虽然通常通过活检进行诊断，但内镜下结肠直肠狭窄可能可以在术前通过人工智能进行预测。已经使用了各种人工智能模型，其合并敏感度为0.857，特异度为0.850。我们发现各种人工智能模型的准确性之间没有统计学上的显著差异。
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