Chaos enhanced grey wolf optimization wrapped ELM for diagnosis of paraquat-poisoned patients

doi:10.1016/j.compbiolchem.2018.11.017

科研成果详情

题名	Chaos enhanced grey wolf optimization wrapped ELM for diagnosis of paraquat-poisoned patients
作者	Zhao, Xuehua 1; Zhang, Xiang 2; Cai, Zhennao 3; Tian, Xin 4; Wang, Xianqin5; Huang, Ying 6; Chen, Huiling 7; Hu, Lufeng8
发表期刊	COMPUTATIONAL BIOLOGY AND CHEMISTRY 影响因子和分区
语种	英语
原始文献类型	Article
关键词	Diagnosis Paraquat Chaos Grey wolf optimization Extreme learning machine
其他关键词	FEATURE-SELECTION ; CLASSIFICATION ; ALGORITHM ; CLASSIFIERS
摘要	Paraquat (PQ) poisoning seriously harms the health of humanity. An effective diagnostic method for paraquat poisoned patients is a crucial concern. Nevertheless, it's difficult to identify the patients with low intake of PQ or delayed treatment. Here, a new efficient diagnostic approach to integrate machine learning and gas chromatography-mass spectrometry (GC-MS), named GEE, is proposed to identify the PQ poisoned patients. First, GC-MS provides the original data that efficiently identified the paraquat-poisoned patients. According to the high dimensionality of the original data, in the second stage, the chaos enhanced grey wolf optimization (EGWO) is adopted to search the optimal feature sets to improve the accuracy of identification. Finally, the extreme learning machine (ELM) is used to identify the PQ poisoned patients. To efficiently evaluate the proposed method, four measures were used in our experiments and comparisons were made with six other methods. The PQ-poisoned patients and robust volunteers can be well identified by GEE and the values of AUC, accuracy, sensitivity and specificity were 95.14%, 93.89%, 94.44% and 95.83%, respectively. Our experimental results demonstrated that GEE had better performance and might serve as a novel candidate diagnosis of PQ-poisoned patients.
资助项目	Science and Technology Plan Project of Wenzhou, China [ZG2017019]; Science and Technology Committee of Shanghai Municipality of China [KF1405]; Zhejiang Provincial Natural Science Foundation of ChinaNatural Science Foundation of Zhejiang Province [LY17F020012, LY14H230001, LY14F020035]; Guangdong Natural Science FoundationNational Natural Science Foundation of Guangdong Province [2018A030313339]; MOE (Ministry of Education in China) Youth Fund Project of Humanities and Social Sciences [17YJCZH261]; Characteristic Innovation Projects of Universities in Guangdong [2017GICTSCX063]; Special Innovation Project of Guangdong Education Department [2017GKTSCX063]; Special Funds for the Cultivation of Scientific, Technological Innovation for College Students in Guangdong [pdjh2018b0861]; 13th Five-Year Plan Project of Philosophy and Social Sciences in Shenzhen [SZ2018D017]
出版者	ELSEVIER SCI LTD
出版地	OXFORD
ISSN	1476-9271
EISSN	1476-928X
卷号	78 页码:481-490
DOI	10.1016/j.compbiolchem.2018.11.017
页数	41
WOS类目	Biology ; Computer Science, Interdisciplinary Applications
WOS研究方向	Life Sciences & Biomedicine - Other Topics ; Computer Science
WOS记录号	WOS:000459524900051
收录类别	SCIE ; EI ; SCOPUS ; PUBMED
发表日期	2019-02
EI入藏号	20184806160756
EI主题词	Diagnosis
URL	查看原文
Pubmed记录号	30501982
Scopus记录号	2-s2.0-85057279588
ESI热点论文	2021-01
ESI高被引论文	2020-01 ; 2020-09 ; 2020-11 ; 2021-01 ; 2021-03 ; 2021-05 ; 2021-07 ; 2021-09 ; 2021-11 ; 2022-01 ; 2022-03 ; 2022-07 ; 2022-09 ; 2022-11 ; 2023-01 ; 2023-03 ; 2023-05 ; 2023-07 ; 2023-09 ; 2023-11 ; 2024-01 ; 2024-03 ; 2024-05
引用统计	被引频次：260[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	https://kms.wmu.edu.cn/handle/3ETUA0LF/10603
专题	药学院（分析测试中心）附属第一医院_药学部药学部
通讯作者	Chen, Huiling; Hu, Lufeng
作者单位	1.Shenzhen Inst Informat Technol, Sch Digital Media, Shenzhen 518172, Peoples R China; 2.Wenzhou Mingcheng Construct Investment Grp Co Ltd, Wenzhou, Peoples R China; 3.Wenzhou Univ, Coll Phys & Elect Informat Engn, Wenzhou 325035, Peoples R China; 4.Chinese Acad Med Sci, Shenzhen Hosp, Canc Hosp, Shenzhen 518000, Peoples R China; 5.Wenzhou Med Univ, Analyt & Testing Ctr, Wenzhou 325000, Peoples R China; 6.Shenzhen Inst Informat Technol, Sch Digital Media, Shenzhen 518172, Peoples R China; 7.Wenzhou Univ, Coll Phys & Elect Informat Engn, Wenzhou 325035, Peoples R China; 8.Wenzhou Med Univ, Affiliated Hosp 1, Dept Pharm, Nanbaixiang St, Wenzhou City 325000, Peoples R China
通讯作者单位	附属第一医院; 药学部药学部
推荐引用方式 GB/T 7714	Zhao, Xuehua,Zhang, Xiang,Cai, Zhennao,et al. Chaos enhanced grey wolf optimization wrapped ELM for diagnosis of paraquat-poisoned patients[J]. COMPUTATIONAL BIOLOGY AND CHEMISTRY,2019,78:481-490.
APA	Zhao, Xuehua., Zhang, Xiang., Cai, Zhennao., Tian, Xin., Wang, Xianqin., ... & Hu, Lufeng. (2019). Chaos enhanced grey wolf optimization wrapped ELM for diagnosis of paraquat-poisoned patients. COMPUTATIONAL BIOLOGY AND CHEMISTRY, 78, 481-490.
MLA	Zhao, Xuehua,et al."Chaos enhanced grey wolf optimization wrapped ELM for diagnosis of paraquat-poisoned patients".COMPUTATIONAL BIOLOGY AND CHEMISTRY 78(2019):481-490.