A VGG19 network with added multi-head self-attention and focal loss reaches 99.25% accuracy for acute lymphoblastic leukemia diagnosis from bone marrow smears.
A hematologist-level deep learning algorithm (bmsnet) for assessing the morphologies of single nuclear balls in bone marrow smears: algorithm development
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Deep Learning with Self-Attention and Enhanced Preprocessing for Precise Diagnosis of Acute Lymphoblastic Leukemia from Bone Marrow Smears in Hemato-Oncology
A VGG19 network with added multi-head self-attention and focal loss reaches 99.25% accuracy for acute lymphoblastic leukemia diagnosis from bone marrow smears.