health
Machine-learning model reconstructs flow cytometry gates from sample records
A medRxiv preprint presents IMPGAT, a method that infers cell-level flow cytometry gating from sample-level cell-frequency annotations. In leukemia datasets, its reported results were comparable to expert variability in ALL and to a supervised model in AML.