Acute Myeloid Leukemia (AML) Detection Using AlexNet Model

Acute Myeloid Leukemia (AML) is a kind of fatal blood cancer with high death rate caused by abnormal cells’ rapid growth in the human body. The usual method to detect AML manual microscopic examination sample, which tedious and time-consuming requires skilled medical operator for accurate detection. In this work, we proposed an AlexNet-based classification model images compared its performance LeNet-5-based Precision, Recall, Accuracy, Quadratic Loss. experiments are conducted on dataset four thousand smear samples. results show that AlexNet was able identify 88.9% correctly 87.4% precision 98.58% accuracy, whereas LeNet-5 identified 85.3% 83.6% 96.25% accuracy.