… cancer at an early stage could help in better and improved treatment. In this research, a deep
… is developed as a method for skin cancer classification. For experimentation, the dataset …

… for classification applications. In the field of medical imaging, there has been a recent trend
toward leveraging the greater potential of deep learning … to use deep learning techniques to …

… imaging, feature extraction and classification of objects. Several types of deep learning
architectures are introduced by so many researchers to classify the lung cancer. In this study, 3D …

… cancer diagnosis and therapy. In this paper, we proposed a stacking ensemble deep learning
… -CNN) to perform a multi-class classification on the five common cancers among women …

… a partitioned deep CNN algorithm for classification of oral cancer filtering into … classification
technique like SVM and DBM methods. The block diagram of proposed image classification …

… that use deep learning to classify the lung … deep learning architectures to classify the lung
lesions into benign and malignant [4]. They are convolutional neural network (CNN), deep …

… to classify breast cancer histopathology images independent of their magnifications. We
present the classification performance of a deep learning … cation level and classify benign and …

… a deep learning approach to cancer detection, and to the identification of genes critical for the
diagnosis of breast cancer… We then used the new representations to classify breast cancer …

… the deep learning network. To the best of our knowledge, XOmiVAE is one of the first activation
level-based interpretable deep learning … of deep learning-based cancer classification and …

… compared to traditional machine learning techniques. In this manuscript, we present a
deep learning approach to accurately detect and classify breast cancer and related sub- …