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National Clinical Research Center for Hematologic Disease, Peking University People's Hospital, Peking University Institute of Hematology
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Achieving an ensemble F1-score of 0.9124, this deep learning model redefines AML diagnosis by aggregating complex cellular data into actionable insights.
Turns out, you can get SOTA crowd instance segmentation by cleverly combining SAM with point supervision and reinforcement learning to select optimal points for mask generation.
