A hybrid CNN-transformer model with multi-task learning achieves 91.3% WBC classification accuracy and 0.72 Pearson correlation for CD16 expression regression from label-free DPC images, augmented by LLM-generated summaries.
Artificial Intelligence in Medicine111, 102005 (2021)
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Towards Label-Free Single-Cell Phenotyping Using Multi-Task Learning
A hybrid CNN-transformer model with multi-task learning achieves 91.3% WBC classification accuracy and 0.72 Pearson correlation for CD16 expression regression from label-free DPC images, augmented by LLM-generated summaries.