… This research work presents lung cancer detection using histopathological images. A
convolutional neural network (CNN) was implemented to classify an image of three different …

… To study the prediction of gene mutations from histopathology images, we modified the
inception v3 to perform multitask classification rather than a single-task classification. Each …

… the applications of CNNs to histopathological images of lung cancer. Furthermore, no public
… on lung cancer detection was only on cytological image [48]. The size of each image was …

… The dataset used in this study contains 15000 lung histopathology images. This dataset is
… lung cancer using histopathological images. The whole dataset consisted of 15000 images …

… based method for detection of lung cancer in whole slide histopathology images. VGG16 and
… have potential to perform lung cancer diagnose from whole slide images, but more effort is …

… It contains lung and colon tissue images, but this work has focused only on the lung cancer
images contained in the dataset. Those images represent zoomed sections of biopsied tissue …

… -L1) treatment for lung cancer is primarily recognized as an … stained pathological images of
lung cancer tissues, as well as to … whole slice images (WSIs) of lung cancer downloaded from …

… for different types of cancers. Also, our results suggest that deep learning of histopathological
imaging features can predict the prognosis of lung cancer patients, thereby assisting health …

… Image classification is a challenging task for the visual content, particularly microscopic images
for example histopathological images … textures present in histopathology of images. Deep …

… Therefore, early and accurate detection of lung cancer histology is an urgent need, and as …
to analyze histopathology images of lung cancer. However, manual analysis of histopathology …