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This study aims to apply one of the artificial intelligence algorithms namely deep learning in the classification process of white blood cell subtypes. Classification of white blood cell subtypes is needed for identification of blood diseases such as leukemia, anemia, etc. The deep learning model used in this study is the LeNet architecture which is easy to implement. After going through the preprocessing of white blood cell microscopic images and classification of datasets according to the method, the classification accuracy was 94%..

The Implementation of Deep Learning for White Blood Cell Subtype Classification from Microscopic Images