SD-CNN: A shallow-deep CNN for improved breast cancer diagnosis-Reference-Cited by-同舟云学术

SD-CNN: A shallow-deep CNN for improved breast cancer diagnosis

Published:2018-12 Issue: Volume:70 Page:53-62
ISSN:0895-6111
Container-title:Computerized Medical Imaging and Graphics
language:en
Short-container-title:Computerized Medical Imaging and Graphics

Author:

Gao Fei,Wu Teresa,Li Jing,Zheng Bin,Ruan Lingxiang,Shang Desheng,Patel Bhavika^ORCID

Publisher

Elsevier BV

Subject

Computer Graphics and Computer-Aided Design,Health Informatics,Computer Vision and Pattern Recognition,Radiology Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Reference45 articles.

1. Multiple Kernel Learning for Breast Cancer Classification;Augusto,2014

2. Deep Learning with Non-medical Training Used for Chest Pathology Identification 94140V;Bar,2015

3. An empirical comparison of voting classification algorithms: bagging, boosting, and variants;Bauer;Mach. Learn.,1999

4. A deep transfer learning approach for improved post-traumatic stress disorder diagnosis;Banerjee,2017

5. Breastcancer.org. (2018). U.S. Breast Cancer Statistics | Breastcancer.org. [online] Available at: https://www.breastcancer.org/symptoms/understand_bc/statistics [Accessed 25 Sep. 2018].

Cited by 156 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A systematic literature analysis of multi-organ cancer diagnosis using deep learning techniques;Computers in Biology and Medicine;2024-09

2. Síntesis de imagen médica postcontraste en estudios de DCE-MRI de mama usando aprendizaje profundo;TecnoLógicas;2024-08-01

3. Prospective Study of Supplemental Screening With Contrast-Enhanced Mammography in Women With Elevated Risk of Breast Cancer: Results of the Prevalence Round;Journal of Clinical Oncology;2024-07-26

4. C-Hybrid-NET: A self-attention-based COVID-19 screening model based on concatenated hybrid 2D-3D CNN features from chest X-ray images;Multimedia Tools and Applications;2024-07-11

5. Developing diverse ensemble architectures for automatic brain tumor classification;Multimedia Tools and Applications;2024-06-24