Deep learning in cancer diagnosis and prognosis prediction: a minireview on challenges, recent trends, and future directions
AB Tufail, YK Ma, MKA Kaabar… - … Methods in Medicine, 2021 - Wiley Online Library
Deep learning (DL) is a branch of machine learning and artificial intelligence that has been
applied to many areas in different domains such as health care and drug design. Cancer …
applied to many areas in different domains such as health care and drug design. Cancer …
Classification of breast cancer histopathological images using DenseNet and transfer learning
Breast cancer is one of the most common invading cancers in women. Analyzing breast
cancer is nontrivial and may lead to disagreements among experts. Although deep learning …
cancer is nontrivial and may lead to disagreements among experts. Although deep learning …
Application of transfer learning and ensemble learning in image-level classification for breast histopathology
Background Breast cancer has the highest prevalence among all cancers in women
globally. The classification of histopathological images in the diagnosis of breast cancers is …
globally. The classification of histopathological images in the diagnosis of breast cancers is …
Breast cancer histopathology image classification based on dual-stream high-order network
The early diagnosis of breast cancer using pathological images is of the vital importance.
Recently, breast cancer histopathology image classification methods based on convolution …
Recently, breast cancer histopathology image classification methods based on convolution …
Dcet-net: Dual-stream convolution expanded transformer for breast cancer histopathological image classification
Y Zou, S Chen, Q Sun, B Liu… - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
Researches on breast cancer histopathological image classification have achieved a great
breakthrough using deep backbones of Convolutional Neural Networks (CNNs) in recent …
breakthrough using deep backbones of Convolutional Neural Networks (CNNs) in recent …
A hybrid lightweight breast cancer classification framework using the histopathological images
D Addo, S Zhou, K Sarpong, OT Nartey… - Biocybernetics and …, 2024 - Elsevier
A crucial element in the diagnosis of breast cancer is the utilization of a classification method
that is efficient, lightweight, and precise. Convolutional neural networks (CNNs) have …
that is efficient, lightweight, and precise. Convolutional neural networks (CNNs) have …
CNN-based hidden-layer topological structure design and optimization methods for image classification
J Liu, H Shao, Y Jiang, X Deng - Neural Processing Letters, 2022 - Springer
Convolutional neural networks (CNN) is one of the most important branches of deep
learning, which always shows the excellent performance on image classification via unique …
learning, which always shows the excellent performance on image classification via unique …
Hyperspectral image classification using Second-Order Pooling with Graph Residual Unit Network
K Sarpong, Z Qin, R Ssemwogerere… - Expert Systems with …, 2024 - Elsevier
Abstract Convolutional Neural Networks (CNNs) have become increasingly popular for
hyperspectral image (HSI) classification due to their ability to capture spatial and spectral …
hyperspectral image (HSI) classification due to their ability to capture spatial and spectral …
Cross-Scale Fusion Transformer for Histopathological Image Classification
SK Huang, YT Yu, CR Huang… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Histopathological images provide the medical evidences to help the disease diagnosis.
However, pathologists are not always available or are overloaded by work. Moreover, the …
However, pathologists are not always available or are overloaded by work. Moreover, the …
Breast Cancer Histopathology Images Classification Through Multi-View Augmented Contrastive Learning and Pre-Learning Knowledge Distillation
J Si, W Jia, H Jiang - IEEE Access, 2024 - ieeexplore.ieee.org
Breast cancer is one of the most common malignant tumors in women, and accurate
classification of benign and malignant breast cancer histopathology images is critical for …
classification of benign and malignant breast cancer histopathology images is critical for …