Abdel Nasser H. Zaied1, Ehab Rushdy2, Mona Gamal3,*
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1349-1364, 2023, DOI:10.32604/csse.2023.033596
Abstract Acute leukemia is an aggressive disease that has high mortality rates worldwide. The error rate can be as high as 40% when classifying acute leukemia into its subtypes. So, there is an urgent need to support hematologists during the classification process. More than two decades ago, researchers used microarray gene expression data to classify cancer and adopted acute leukemia as a test case. The high classification accuracy they achieved confirmed that it is possible to classify cancer subtypes using microarray gene expression data. Ensemble machine learning is an effective method that combines individual classifiers to classify new samples. Ensemble classifiers… More >
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