节的
甲状腺癌
组织病理学
卷积神经网络
医学
淋巴
乳头状癌
原发性肿瘤
癌
病理
放射科
内科学
肿瘤科
人工智能
甲状腺
转移
计算机科学
癌症
作者
Antoinette Esce,Jordan P. Redemann,Andrew C. Sanchez,Garth T. Olson,Joshua A. Hanson,Shweta Agarwal,Nathan H. Boyd,David Martin
标识
DOI:10.1016/j.amjsurg.2021.05.002
摘要
The presence of nodal metastases is important in the treatment of papillary thyroid carcinoma (PTC). We present our experience using a convolutional neural network (CNN) to predict the presence of nodal metastases in a series of PTC patients using visual histopathology from the primary tumor alone.174 cases of PTC were evaluated for the presence or absence of lymph metastases. The artificial intelligence (AI) algorithm was trained and tested on its ability to discern between the two groups.The best performing AI algorithm demonstrated a sensitivity and specificity of 94% and 100%, respectively, when identifying nodal metastases.A CNN can be used to accurately predict the likelihood of nodal metastases in PTC using visual data from the primary tumor alone.
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