文献类型：期刊文献

中文题名：基于多目标量子优化分类器的急诊危重患者关键指标筛选*

英文题名：Screening Critical Patients with Optimized Classifier Based on Multi Objective Quantum

作者：Jing, Li[1]; Shuxiao, Pan[1]; Xueyan, Li[2]; Lijing, Jia[3]; Yuzhuo, Zhao[3]

第一作者：Jing, Li

机构：[1] School of Economics and Management, Beijing Jiaotong University, Beijing, 100044, China; [2] Management College, Beijing Union University, Beijing, 100101, China; [3] The General Hospital of the People’s Liberation Army, Beijing, 100853, China

第一机构：School of Economics and Management, Beijing Jiaotong University, Beijing, 100044, China

年份：2019

卷号：3

期号：12

起止页码：101-112

外文期刊名：Data Analysis and Knowledge Discovery

收录：EI(收录号：20240615490682)

语种：中文

外文关键词：Diagnosis - Multiobjective optimization

摘要：[Objective] This study tries to improve the identification of emergency patients’ critical indicators. [Methods] First, we selected a swarm algorithm with multi-objective particle and quantum behaviors. Then, we combined this algorithm with machine learning classifier to propose a new method for screening the needed indicators. Finally, we compared the new method with two existing ones. [Results] The proposed method increased search scope and reduced data dimensionality, which help us obtain indicators of clinical significance. [Limitations] The calculation of indicators’ importance needs to be optimized with recursive method. [Conclusions] The proposed method could improve the recognition rates of critical patients. ? 2019 Data Analysis and Knowledge Discovery.