  Lung and Colon cancer are one of the leading causes of mortality and
morbidity in adults. Histopathological diagnosis is one of the key components
to discern cancer type. The aim of the present research is to propose a
computer aided diagnosis system for diagnosing squamous cell carcinomas and
adenocarcinomas of lung as well as adenocarcinomas of colon using convolutional
neural networks by evaluating the digital pathology images for these cancers.
Hereby, rendering artificial intelligence as useful technology in the near
future. A total of 2500 digital images were acquired from LC25000 dataset
containing 5000 images for each class. A shallow neural network architecture
was used classify the histopathological slides into squamous cell carcinomas,
adenocarcinomas and benign for the lung. Similar model was used to classify
adenocarcinomas and benign for colon. The diagnostic accuracy of more than 97%
and 96% was recorded for lung and colon respectively.
