A GNN-infused set transformer with farthest-point-sampled inducing points achieves the best reported F1 for automated MRD detection in flow cytometry data.
Proceed- ings of the National Academy of Sciences111(26), E2770–E2777 (2014)
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On the importance of local and global feature learning for automated measurable residual disease detection in flow cytometry data
A GNN-infused set transformer with farthest-point-sampled inducing points achieves the best reported F1 for automated MRD detection in flow cytometry data.