甲状腺结节
医学
活检
细针穿刺
甲状腺
穿刺活检
放射科
普通外科
结核(地质)
内科学
生物
古生物学
作者
Jue D. Wang,Nafen Zheng,Huan Wan,Qinyue Yao,Shijun Jia,Xin Zhang,Sha Fu,Jingliang Ruan,Gui He,Xulin Chen,Suiping Li,Rui Chen,Boan Lai,Jin Wang,Qingping Jiang,Nengtai Ouyang,Yin Zhang
标识
DOI:10.1016/s2589-7500(24)00085-2
摘要
Accurately distinguishing between malignant and benign thyroid nodules through fine-needle aspiration cytopathology is crucial for appropriate therapeutic intervention. However, cytopathologic diagnosis is time consuming and hindered by the shortage of experienced cytopathologists. Reliable assistive tools could improve cytopathologic diagnosis efficiency and accuracy. We aimed to develop and test an artificial intelligence (AI)-assistive system for thyroid cytopathologic diagnosis according to the Thyroid Bethesda Reporting System.
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