Improving Classification of Cell Types in Acute Myeloid Leukemia with Self-guided Masking
Published in Preprint, 2026
This research presents a novel computational approach utilizing self-guided masking techniques to enhance the classification of cell types in Acute Myeloid Leukemia. The proposed methodology aims to improve diagnostic accuracy and representation learning in complex biomedical sequencing data.
Recommended citation: Naziri, A., Asgari, A., Sachlos, E., An, A., & Seyyed-Kalantari, L. (2024). "Improving Classification of Cell Types in Acute Myeloid Leukemia with Self-guided Masking." Preprint.
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