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Leukemia is a complex and life-threatening disease that necessitates accurate and early diagnosis for effective treatment. Deep learning techniques have emerged as promising tools for medical diagnosis, including the detection of leukemia. My aim is to investigate the potential of deep learning in leukemia diagnosis. The book commences with an extensive literature review, examining conventional diagnostic methods and their limitations. It subsequently introduces deep learning as a promising approach in medical diagnosis, highlighting previous studies focused on deep learning-based leukemia diagnosis. The methodology section outlines the data set utilized for training and evaluation, elucidating the preprocessing steps implemented to ensure data quality. The deep learning model architecture is described, along with the specifics of the training process, including hyperparameter tuning.
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