基于深度學(xué)習(xí)的急性白血病流式細(xì)胞術(shù)檢測報(bào)告文本資料自動(dòng)分類研究

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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

流式細(xì)胞術(shù)（flowcytometry，F(xiàn)CM）是一種能精確且快速分析細(xì)胞或者生物微粒理化性質(zhì)的檢測技術(shù)，被業(yè)內(nèi)稱為生物實(shí)驗(yàn)室的"CT"[1-3]。（剩余7604字）