Despite technological and medical advances, the detection, interpretation, and treatment of
cancer based on imaging data continue to pose significant challenges. These include inter …

Despite technological and medical advances, the detection, interpretation, and treatment of
cancer based on imaging data continue to pose significant challenges. These include high …

Simple Summary In early-stage lung cancer surgery, determining the extent of resection
relies on microscopic examination of frozen sections (FSs), especially when the histology is …

Optical coherence tomography (OCT) is being investigated in breast cancer diagnostics as a
real-time histology evaluation tool. We present a customized deep convolutional neural …

We demonstrate a convolutional neural network (CNN) for multi-class breast tissue
classification as adipose tissue, benign dense tissue, or malignant tissue, using multi …

Abstract Advancements in Machine Learning (ML) and Computer Vision have led to notable
improvements in the detection of breast cancer. However, the accuracy of the classifier is …

Background The impact and utility of machine learning (ML)-based prediction tools for
cancer outcomes including assistive diagnosis, risk stratification, and adjunctive decision …

生成对抗网络(Generative Adversarial Nets, GANs) 模型可以无监督学习到更丰富的数据信息,
其包括生成模型与判别模型, 凭借二者之间的对抗提高性能. 针对传统GANs 存在着梯度消失 …

Breast cancer is the most common type of cancer affecting women. The formation of lumps in
the breast is one of the first signs of the presence of this disease. These tumors can either be …