Advancements in Early Lung Cancer Detection Using Convolutional Neural Networks

It presents a groundbreaking approach for lung cancer detection utilizing Convolutional Neural Networks. Cancer remains a leading cause of global morbidity and mortality, underscoring the urgency for accurate and timely diagnostics. Leveraging the power of deep learning, our proposed CNN-based model demonstrates exceptional efficacy in analyzing medical imaging data, particularly chest radiographs, to identify subtle patterns indicative of lung malignancies. The model's architecture integrates advanced features for feature extraction and classification, enhancing sensitivity and specificity in comparison to conventional methods. Through extensive validation on diverse datasets, our CNN exhibits robust performance, showcasing its potential as a reliable tool for early and precise lung cancer detection. The implementation of this technology has significant implications for improving patient outcomes by facilitating earlier interventions and personalized treatment strategies in the fight against lung cancer.