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Screening Critical Patients with Optimized Classifier Based on Multi Objective Quantum |
Jing Li1,Shuxiao Pan1,Xueyan Li2(),Lijing Jia3,Yuzhuo Zhao3 |
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 |
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Abstract [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.
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Received: 01 July 2019
Published: 25 December 2019
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Corresponding Authors:
Xueyan Li
E-mail: gongye1632006@163.com
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