1 School of Economics and Management, Beijing Jiaotong University, Beijing100044, China 2 Management College, Beijing Union University, Beijing100101, China 3 The General Hospital of the People’s Liberation Army, Beijing100853, China
[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.
李静,潘舒笑,李雪岩,贾立静,赵宇卓. 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 *[J]. 数据分析与知识发现, 2019, 3(12): 101-112.
Jing Li,Shuxiao Pan,Xueyan Li,Lijing Jia,Yuzhuo Zhao. Screening Critical Patients with Optimized Classifier Based on Multi Objective Quantum. Data Analysis and Knowledge Discovery, DOI：10.11925/infotech.2096-3467.2019.0776.
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