Paper Title
Lung Cancer Detection on Histopathological Images Using VGG19

Abstract
Lung cancer remains one of the most prevalent and deadly forms of cancer globally. Early detection is crucial for improving patient outcomes and survival rates. This paper explores the application of deep learning techniques, specifically the VGG19 Convolutional Neural Network (CNN) model, to classify histopathological images of lung tissue into three categories: squamous cell carcinoma, adeno carcinoma, and benign tissue. The proposed model leverages VGG19's feature extraction capabilities to achieve high accuracy in detecting and classifying lung cancer from histopathological images, offering a promising approach for automated and efficient diagnosis. Keywords - Lung Cancer, Histopathological Images, Deep Learning, CNN, VGG19.