基于深度学习的急性白血病流式细胞术检测报告文本资料自动分类研究

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Automatic Classification of TextData forFlow Cytometry Detection of Acute Leukemia Based on Deep Learning

ZHANGYazhou]，LIZhiwei2，NONGWeixia3，LEIWei'，BAIWenli'，LIYinzhenl，IRui，WANGKui

DepartmentofPreventiveMedicine，Shihezi UniversitySchoolofMedicine，Shihezi832ooo，Xinjiang，China；

2.ClinicalTestingCenterPeople'sHospitalofijiangUygurutonomousRegion，Urumqi30，injangin；

3.DepartmentofRheumatologyandHematology，ShiheziUniversitySchoolofMedicine，Shhezi832Ooo，Xinjiang，China）

Abstract：OjecieTexloeteclasifiationfectofelangodelontextdataofowcytometreportresultsMethodsSixdep learningmodelsuchsndSeredtalthtetdtaoftesultsffoomeortsifdprdcttit withacuteeukeiandiallaateodelopresivedeFRsultsesialldForf BiLSTMmixedmodelwerethebest，whichwere0.7422，0.7365andO.7361，respectively，andtheF1scoreofthemodelreached 70 % inseven categories：olaeutbskdodlllol plasmacellaboaidotiboaliCocsiododelsdtosiaooftetataiuls flocyometrsreportndombdievousdiestouildoopleeutomatedferalssr improve the efficiency and accuracy of flow cytometry analysis.

Key Words：Flow cytometry； Text classification； CNN； Automated analysis； Deep learning

流式细胞术（flowcytometry，FCM）是一种能精确且快速分析细胞或者生物微粒理化性质的检测技术，被业内称为生物实验室的"CT"[1-3]。（剩余7604字）