Robust multi-phase framework for breast cancer detection and classification using mammogram images with stacked ensemble learning

Key Points

• Detection and classification accuracy improved significantly with ensemble learning techniques, enhancing diagnostic capabilities.
• The framework incorporates multiple algorithms and leverages mammogram images for effective breast cancer surveillance.
• Employing a stacked ensemble learning approach allows for greater accuracy in cancer detection compared to traditional methods.
• These findings suggest potential advancements in early cancer diagnosis and treatment planning based on enhanced imaging analysis.