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HemaGraph: Breaking Barriers in Hematologic Single Cell Classification with Graph Attention
March 1, 2024, 5:43 a.m. | Lorenzo Bini, Fatemeh Nassajian Mojarrad, Thomas Matthes, St\'ephane Marchand-Maillet
cs.LG updates on arXiv.org arxiv.org
Abstract: In the realm of hematologic cell populations classification, the intricate patterns within flow cytometry data necessitate advanced analytical tools. This paper presents 'HemaGraph', a novel framework based on Graph Attention Networks (GATs) for single-cell multi-class classification of hematological cells from flow cytometry data. Harnessing the power of GATs, our method captures subtle cell relationships, offering highly accurate patient profiling. Based on evaluation of data from 30 patients, HemaGraph demonstrates classification performance across five different cell …
abstract advanced arxiv attention breaking cells class classification cs.lg data flow framework graph networks novel paper patterns q-bio.cb q-bio.qm tools type
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