output
20202025
most citedHard Sample Aware Noise Robust Learning for Histopathology Image Classification

134 citations

5 papers

cs.IR2025★ 2 cited

MixDec Sampling: A Soft Link-based Sampling Method of Graph Neural Network for Recommendation

Xiangjin Xie, Yuxin Chen, Ruipeng Wang +8

Graph neural networks have been widely used in recent recommender systems, where negative sampling plays an important role. Existing negative sampling methods restrict the relation…

cs.AI2024★ 4 cited

Methodology and Real-World Applications of Dynamic Uncertain Causality Graph for Clinical Diagnosis with Explainability and Invariance

Zhan Zhang, Qin Zhang, Yang Jiao +18

AI-aided clinical diagnosis is desired in medical care. Existing deep learning models lack explainability and mainly focus on image analysis. The recently developed Dynamic Uncerta…

eess.IV2021★ 134 cited

Hard Sample Aware Noise Robust Learning for Histopathology Image Classification

Chuang Zhu, Wenkai Chen, Ting Peng +2

Deep learning-based histopathology image classification is a key technique to help physicians in improving the accuracy and promptness of cancer diagnosis. However, the noisy label…

eess.IV2021★ 69 cited

Predicting Axillary Lymph Node Metastasis in Early Breast Cancer Using Deep Learning on Primary Tumor Biopsy Slides

Feng Xu, Chuang Zhu, Wenqi Tang +7

Objectives: To develop and validate a deep learning (DL)-based primary tumor biopsy signature for predicting axillary lymph node (ALN) metastasis preoperatively in early breast can…

cs.CV2020★ 25 cited

Dual-Sampling Attention Network for Diagnosis of COVID-19 from Community Acquired Pneumonia

Xi Ouyang, Jiayu Huo, Liming Xia +15

The coronavirus disease (COVID-19) is rapidly spreading all over the world, and has infected more than 1,436,000 people in more than 200 countries and territories as of April 9, 20…