Abstract:
Lung cancer remains a leading cause of cancer mortality, emphasizing the
importance of early and accurate diagnosis. This study proposes an attention-
based CNN model to enhance lung cancer classification from CT scans. The
attention mechanism improves the model’s focus on critical regions, boosting
diagnostic accuracy. Experiments on the IQ-OTH/NCCD and Lung Cancer Type
datasets achieved classification accuracies of 99.65% and 98.3%, respectively,
demonstrating significant performance improvements in distinguishing between
cancer types and cases
