首页|期刊导航|大数据挖掘与分析（英文版）|Multimodal Nested Attention Network for Lymph Node Metastasis Prediction of Thyroid Carcinoma

Multimodal Nested Attention Network for Lymph Node Metastasis Prediction of Thyroid Carcinoma

Guojun Li Chulin Sha Min He Jincao Yao Chanjuan Peng Yinjie Hu Xuhan Feng Jianfeng Yang Xingyu Gao Dong Xu Xiaolin Li

大数据挖掘与分析（英文版）2026，Vol.9Issue(1)：178-197,20.

大数据挖掘与分析（英文版）2026，Vol.9Issue(1)：178-197,20.DOI:10.26599/BDMA.2025.9020046

Multimodal Nested Attention Network for Lymph Node Metastasis Prediction of Thyroid Carcinoma

Guojun Li ¹Chulin Sha ²Min He ²Jincao Yao ³Chanjuan Peng ⁴Yinjie Hu ²Xuhan Feng ²Jianfeng Yang ⁵Xingyu Gao ⁶Dong Xu ³Xiaolin Li²

作者信息

1. Academy of Medical Engineering and Translational Medicine,Tianjin University,Tianjin 300072,China||Hangzhou Institute of Medicine,Chinese Academy of Sciences,Hangzhou 310000,China
2. Hangzhou Institute of Medicine,Chinese Academy of Sciences,Hangzhou 310000,China
3. Zhejiang Cancer Hospital,Hangzhou 310022,China
4. Zhejiang Cancer Hospital,Hangzhou 310022,China||Department of Ultrasound,Women's Hospital,Zhejiang University School of Medicine,Hangzhou 310000,China
5. Shaoxing People's Hospital,Shaoxing 312000,China
6. Institute of Microelectronics,Chinese Academy of Sciences,Beijing 100029,China||Institute of Microelectronics,University of Chinese Academy of Sciences,Beijing 100049,China
折叠

摘要

关键词

multimodal learning/deep learning/thyroid cancer/Lymph Node Metastasis(LNM)/UltraSound(US)/Computed Tomography(CT)

Key words

multimodal learning/deep learning/thyroid cancer/Lymph Node Metastasis(LNM)/UltraSound(US)/Computed Tomography(CT)

引用本文复制引用

Guojun Li,Chulin Sha,Min He,Jincao Yao,Chanjuan Peng,Yinjie Hu,Xuhan Feng,Jianfeng Yang,Xingyu Gao,Dong Xu,Xiaolin Li..Multimodal Nested Attention Network for Lymph Node Metastasis Prediction of Thyroid Carcinoma[J].大数据挖掘与分析（英文版）,2026,9(1):178-197,20.

基金项目

This work was supported by the Science and Technology Innovation(STI)2030—Major Projects(No.2022ZD0208700),the National Natural Science Foundation of China(Nos.32200524,62376264,62475239,and 82071946),the Natural Science Foundation of Zhejiang Province(No.LZY21F030001),the Pioneer and Leading Goose R&D Program of Zhejiang(No.2023C04039),the National Key Research and Development Program of China(No.2022YFF0608403),the Zhejiang Province Medical and Health Science and Technology Project(No.2023KY581),and the Zhejiang Leading Innovation and Entrepreneurship Team(No.2022R01006).We thank Yuan Gao for providing us external validation set. （STI）

大数据挖掘与分析（英文版）

访问量0

下载量0

段落导航