A hybrid framework integrating Fuzzy K-means segmentation and CNN feature extraction with SVM kernel for lung cancer classification

Key Points

• Lung cancer classification accuracy improves with the introduced hybrid framework combining fuzzy k-means and CNN feature extraction.
• A significant performance boost is reported with the SVM kernel integration, enhancing model capabilities.
• Assessment involves machine learning algorithms, particularly emphasizing the role of feature extraction techniques in classification tasks.
• The findings highlight the potential for more precise diagnoses, though further validation is needed to confirm clinical applicability.