Deep Learning-Based CAD System for Multi-Class Lung Cancer Detection and Classification from Histopathological Images

Lung cancer is one of the main causes of cancer-related fatalities worldwide, which underscores how crucial early and precise diagnosis procedures are to improve patient outcomes. The present diagnostic technologies have a variety of limitations, such as high false-positive rates, limited accuracy, and the requirement for professional interpretation. This study provides a state-of-the-art Computer-Aided Design (CAD) system that uses histopathology pictures to diagnose and categorize lung cancer using a mix of state-of-the-art deep learning algorithms. The performed analysis demonstrates the potential of deep learning-driven CAD systems to boost early diagnosis rates and assist pathologists by considerably enhancing lung cancer detection accuracy in clinical settings.