Abstract

This study introduces a hybrid approach for lung cancer detection, combining Neuro-Fuzzy Systems for robust feature extraction and the Firefly Algorithm for accurate classification of lung nodules as benign or malignant. The methodology is validated through comprehensive experiments using standard datasets and compared against established techniques like SVM-ANN and RBF-PSO. The research highlights the interpretability and learning capabilities of Neuro-Fuzzy Systems and the effectiveness of the Firefly Algorithm in medical image classification, showcasing improvements in accuracy and reliability over traditional methods.