摘要
阐述人工智能技术比较睡眠呼吸暂停综合征(SAS)患者的血氧饱和度指标与健康人群之间指标的差异性,选择患者血氧的最佳指标,对每段数据计算多种特征并分析差异,使用人工智能领域中的人工蜂群算法优化支持向量机相关参数的模型。
This paper describes the difference between the blood oxygen saturation index of patients with sleep apnea syndrome(SAS) and that of healthy people using artificial intelligence technology,selects the best index of the patient’s blood oxygen, calculates multiple features for each segment of data and analyzes the differences, and uses the artificial bee colony algorithm in the field of artificial intelligence to optimize the model of support vector machine related parameters.
作者
熊馨
冯建楠
王春武
刘瑞湘
贺建峰
XIONG Xin;FENG Jiannan;WANG Chunwu;LIU Ruixiang;HE Jianfeng(Kunming University of Technology,Yunnan 650500,China;Department of Physics and Electronic Engineering,Hanshan Normal University,Guangdong 521000,China;Clinical Psychology Department of the 2nd People's Hospital of Yunnan,Yunnan 650021,China.)
出处
《电子技术（上海）》
2023年第1期216-217,共2页
Electronic Technology
关键词
人工智能
支持向量机
特征分类
artificial intelligence
support vector machine
feature classification
