Leukemia Classification using a Convolutional Neural Network of AML Images
Keywords:Leukemia, classification, CNN, AML, ALL-ADB1
Among the most pressing issues in the field of illness diagnostics is identifying and diagnosing leukemia at its earliest stages, which requires accurate distinction of malignant leukocytes at a low cost. Leukemia is quite common, yet laboratory diagnostic centres often lack the necessary technology to diagnose the disease properly, and the available procedures take a long time. They are considering the efficacy of machine learning (ML) in illness diagnostics and that deep learning as a machine learning method is becoming critical. This study proposes a convolutional neural network (CNN) deep learning model for leukemia diagnosis utilizing the AML (acute myeloid leukemia) dataset. The classification using the proposed method achieved results that exceeded 98% accuracy, the sensitivity of 94.73% and specificity of 98.87%.
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Copyright (c) 2023 MUHAMMAD SAFWAN ABD AZIZ, Karrar A. Kadhim, Fallah H Najjar, Ali Abdulhussein Waad, Ibrahim H Al-Kharsan, Zaid Nidhal Khudhair, Ali Aqeel Salim
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