The growing prevalence of acute lymphoblastic leukemia cancer worldwide underlines the critical need for early and more precise detection to counter this deadly disease. This study presents a robust SqueezeNet-enhanced machine learning framework for automatically screening and classifying histopathological images for acute lymphoblastic leukemia. This work employs a deep learning (DL)-based SqueezeNet integrated with three machine learning (ML) models including neural network (NN), …