计算机科学
淋巴细胞
周转时间
人口
流式细胞术
质量保证
细胞仪
鉴定(生物学)
门控
数据挖掘
医学
免疫学
生物
病理
生理学
植物
外部质量评估
环境卫生
操作系统
作者
M. Zhang,Yali Zhang,Jingwen Zhang,J. Zhang,SiYuan Gao,Li Zhengqiang,Kai Xiong Tao,XiaoDan Liang,Jianhua Pan,Min Zhu
标识
DOI:10.1515/cclm-2023-1141
摘要
Lymphocyte subsets are the predictors of disease diagnosis, treatment, and prognosis. Determination of lymphocyte subsets is usually carried out by flow cytometry. Despite recent advances in flow cytometry analysis, most flow cytometry data can be challenging with manual gating, which is labor-intensive, time-consuming, and error-prone. This study aimed to develop an automated method to identify lymphocyte subsets.
科研通智能强力驱动
Strongly Powered by AbleSci AI