NAS-SGAN: A Semi-supervised Generative Adversarial Network Model for Atypia Scoring of Breast Cancer Histopathological Images-Reference-Cited by-同舟云学术

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NAS-SGAN: A Semi-supervised Generative Adversarial Network Model for Atypia Scoring of Breast Cancer Histopathological Images

Published:2021 Issue: Volume: Page:1-1
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Das Asha,Devarampati Vinod Kumar,Nair Madhu S.

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

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

Link

http://xplorestaging.ieee.org/ielx7/6221020/6363502/09627629.pdf?arnumber=9627629

Cited by 15 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. TNCB: Tri-Net With Cross-Balanced Pseudo Supervision for Class Imbalanced Medical Image Classification;IEEE Journal of Biomedical and Health Informatics;2024-04

2. SGAN-SAM-ERNIE: A Novel and Effective Detection Scheme for Chinese Fake Reviews;IEEE Access;2024

3. Histopathological Image Diagnosis for Breast Cancer Diagnosis Based on Deep Mutual Learning;Diagnostics;2023-12-31

4. Molecular-subtype guided automatic invasive breast cancer grading using dynamic contrast-enhanced MRI;Computer Methods and Programs in Biomedicine;2023-12

5. Future Practices of Breast Pathology Using Digital and Computational Pathology;Advances in Anatomic Pathology;2023-09-22

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