… histopathology analyses. We elaborate on biases which are typically inherent in histopathological
image … available haematoxylin-eosin-stained images of various tumour entities, we …

… lung cancers are graded. Therefore, by grouping histopathological images of lung cancer
with similar features, we could arrive at a possible conclusion that images belonging to the …

… cancer is the key to improving the survival rate of patients. A method of breast cancer
histopathological images … (2.26 million cases of breast cancer and 2.2 million cases of lung …

… Classification and mutation prediction from non-small cell lung cancer histopathology
images using deep learning. Nat Med 2018; 24: 1559–67. doi: 10.1038/s41591-018-0177-5. …

… to analyze cancer disorders, particularly colon and lung cancers. … diagnose various cancers
using histopathology image processing… the photos of colon and lung cancer into five groups: …

… In order to precisely separate mitotic nuclei from histopathology images of colon and lung
tumor… mitotic nuclei in colon and lung cancer histopathology images by taking advantage of the …

… on the histopathological morphology of liver cancer due to its … for liver cancer histopathological
image classification using … of detailed cancer region annotations in those images, patch …

… CAD has been successfully applied in breast cancer, cervical cancer, prostate cancer
and lung cancer analysis 6 . Arevalo et al. have presented a review on automatic …

… supervised tissue classification of CRC histological images. Second, they … -cancer types
(ie, predictions of transcriptomic mRNA expression levels and genomic mutations in lung cancer …

… First, we present the results associated with cancer detection for histopathological images.
In the context of evaluating the performance of classification models within machine learning, …