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What is Deep CNN for Blood Cancer Classification about?

This study presents a novel approach for multiclass blood cancer classification, specifically focusing on Acute Lymphoblastic Leukemia (ALL), using deep convolutional neural networks (CNN) and optimized feature extraction techniques. The research achieved a maximum accuracy of 99.84% by integrating ResNet50 CNN architecture with feature selection algorithms like Particle Swarm Optimization and Cat Swarm Optimization. The proposed model aims to enhance the accuracy and efficiency of blood cancer diagnosis, a

Author

afridamuskaan

Language

EN