… with early detection of the cancer so that appropriate intervention … classification algorithm
by fusing a number of deep learning approaches has been proposed to detect prostate cancer …

… However, the histopathological analysis of breast cancer is non-trivial, labor-… deep
learning approach for the definite classification of non-carcinoma and carcinoma breast cancer …

… Melanoma accounts for 4% of the new cancer cases diagnosed in the UK annually. This …
This paper proposes a classification framework using the innovations made in deep learning. …

… task of four-class classification of breast cancer histology images. Here we present a deep
learning framework for the task of multi-class breast cancer histology image classification. Our …

… by diagnosing cancer is important in reducing the risk of death. In this paper, classification
of lung nodules is performs using CT images of SPIE-AAPM-LungX data. Deep learning has …

… a deep learning method for liver cancer histopathological image classification using only …
data, this paper proposes a deep learning method for the classification of liver histopathological …

… In this paper, the CNN-based skin cancer classification was presented, which is considered
a good feature extractor algorithm compared to the DNN. The proposed models do not need …

… In this paper, a novel deep learning model for improving the classification results on the
MIAS dataset was proposed. The purpose of this model is to help medical doctors in BC detec…

… in lung cancer. … ) to classify the most common lung cancer subtypes, pulmonary
adenocarcinoma (ADC), pulmonary squamous cell carcinoma (SqCC), and small-cell lung cancer …

… In this paper, we attempt to use deep neural networks to ensemble five classification models,
which are kNN, SVMs, DTs, RFs and gradient boosting decision trees (GBDTs), to construct …