Dual-Input Transformer: An End-to-End Model for Preoperative Assessment of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer Ultrasonography-Reference-Cited by-同舟云学术

Dual-Input Transformer: An End-to-End Model for Preoperative Assessment of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer Ultrasonography

Published:2023-01 Issue:1 Volume:27 Page:251-262
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Tong Tong¹^ORCID,Li Dongyang²,Gu Jionghui³,Chen Guo⁴,Bai Guotao⁴,Yang Xin¹,Wang Kun¹^ORCID,Jiang Tianan³^ORCID,Tian Jie¹^ORCID

Affiliation:

1. CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China

2. Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, Beijing, China

3. Department of Ultrasound, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China

4. China Mobile Information Technology Center, Beijing, China

Funder

Ministry of Science and Technology of China

National Natural Science Foundation of China

Beijing Science Fund for Distinguished Young Scholars

Excellent Member Project of Youth Innovation Promotion Association CAS

Scientific Research Fund of Zhejiang Provincial Education Department

High-Level Talents Team Introduction in Zhuhai City

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Health Informatics

Link

http://xplorestaging.ieee.org/ielx7/6221020/10006388/09925581.pdf?arnumber=9925581

Reference32 articles.

1. Ultrasound-based deep learning radiomics in the assessment of pathological complete response to neoadjuvant chemotherapy in locally advanced breast cancer

2. Assessing PD-L1 expression in non-small cell lung cancer and predicting responses to immune checkpoint inhibitors using deep learning on computed tomography images

3. Deep learning radiomics of ultrasonography can predict response to neoadjuvant chemotherapy in breast cancer at an early stage of treatment: a prospective study

4. Early Prediction of Response to Neoadjuvant Chemotherapy in Breast Cancer Sonography Using Siamese Convolutional Neural Networks

5. Squeeze-and-Excitation Networks

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