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A Hybrid Deep Learning Framework with Explainable AI for Lung Cancer Classification with DenseNet169 and SVM

arXiv — cs.CV•Thursday, December 4, 2025 at 5:00:00 AM
PositiveArtificial Intelligence
  • A new study has introduced a hybrid deep learning framework utilizing DenseNet169 and SVM for the classification of lung cancer, aiming to improve detection accuracy and interpretability through advanced AI techniques. The framework employs the IQOTHNCCD lung cancer dataset and incorporates methods like Focal Loss and Feature Pyramid Networks for enhanced performance.
  • This development is significant as it addresses the critical need for early lung cancer diagnosis, which is essential for improving patient survival rates. The automated classification system reduces the time and potential errors associated with manual interpretation of CT scans.
  • The integration of explainable AI techniques, such as Grad-CAM and SHAP, highlights a growing trend in the medical field towards transparency in AI-driven diagnostics. This reflects a broader movement to enhance the reliability of AI systems in healthcare, ensuring that practitioners can understand and trust the decisions made by these technologies.
— via World Pulse Now AI Editorial System
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