Artificial intelligence-based pathological application to predict regional lymph node metastasis in Papillary Thyroid Cancer

被引:1
作者
Sun, Dawei [1 ]
Li, Huichao [1 ]
Wang, Yaozong [3 ]
Li, Dayuan [2 ]
Xu, Di [2 ]
Zhang, Zhoujing [1 ,2 ,3 ]
机构
[1] Qingdao Univ, Affiliated Hosp, Qingdao, Peoples R China
[2] Univ Chinese Acad Sci, Ningbo Inst Mat Technol & Engn, Ningbo, Peoples R China
[3] Univ Chinese Acad Sci, Ningbo Huamei Hosp, Ningbo Hosp 2, Ningbo, Peoples R China
关键词
Artificial intelligence (AI); Neural network; Papillary thyroid cancer; Secondary malignant tumors of lymph nodes; IMAGES; MANAGEMENT; IMPACT; FROZEN; VOLUME;
D O I
10.1016/j.currproblcancer.2024.101150
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
In this study, a model for predicting lymph node metastasis in papillary thyroid cancer was trained using pathology images from the TCGA(The Cancer Genome Atlas) public dataset of papillary thyroid cancer, and a front-end inference model was trained using our center's dataset based on the concept of probabilistic propagation of nodes in graph neural networks. Effectively predicting whether a tumor will spread to regional lymph nodes using a single pathological image is the capacity of the model described above. This study demonstrates that regional lymph nodes in papillary thyroid cancer are a common and predictable occurrence, providing valuable ideas for future research.
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页数:14
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