… The same computer vision can be used in healthcare diagnostics to recognize lung cancer
… dangerous diseases as lung cancer from the histopathological images. Convolutional Neural …

… Classification and mutation prediction from non–small cell lung cancer histopathology images
using deep learning. Nature medicine, 24(10):1559–1567, 2018. 6 [5] Michaël Defferrard, …

… Histopathological image analysis is the gold standard to diagnose cancer. Carcinoma is
a … of hash-based image retrieval techniques to distinguish lung cancer subtypes. Hashing-based …

… -small-cell lung cancer (NSCLC). However, due to the gigapixel of whole slide images (WSIs)
and … With respect to the characteristics of histopathological images, we design a two-stage …

… predicting lung cancer using histopathological images. Early detection of lung cancer surely
… but it is more difficult to identify the lung cancer in the beginning stage itself. The proposed …

… feature extraction from lung and colon cancer histopathological images are presented. …
histopathological imaging with deep learning methods can greatly help patients with lung cancer…

… cancers of TCGA, we can obtain a large number of sequence and image data of patients with
non-small cell lung cancer… unexplored features in histopathological images that have been …

… It is worth to note that histopathology images from lung cancer patients are core-needle
biopsy samples rather than surgery samples as in our training set. This may explain the slightly …

… image dataset (LC25000) with 25,000 color images in 5 classes. Each class contains 5,000
images of the following histologic … colonic tissue, lung adenocarcinoma, lung squamous cell …

… resolution of Whole Slide Histopathological Images (WSIs) makes … Whole Slide
Histopathological Images Survival Analysis … on two cancer subtypes of brain and lung cancer in …