This paper introduces FlowCyt, a benchmark for multi-class single-cell classification in flow cytometry data. The authors showcase the effectiveness of Graph Neural Networks (GNNs) in exploiting spatial relationships for superior performance.
FlowCyt presents a benchmark for multi-class single-cell classification in flow cytometry data, showcasing the effectiveness of Graph Neural Networks (GNNs) in exploiting spatial relationships.
FlowCyt presents a benchmark for multi-class single-cell classification in flow cytometry data, emphasizing the importance of graph neural networks for superior performance.