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 1; Chen, Huiling 3; Hu, Lufeng6
发表日期	2019-02
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
EI入藏号	20184806160756
EI主题词	Diagnosis
URL	查看原文
PubMed ID	30501982
SCOPUSEID	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 ; 2024-07 ; 2024-09 ; 2024-11
通讯作者地址	[Chen, Huiling]College of Physics and Electronic Information Engineering,Wenzhou University,Wenzhou,325035,China
Scopus学科分类	Structural Biology;Biochemistry;Organic Chemistry;Computational Mathematics
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）第一临床医学院（信息与工程学院）、附属第一医院附属第一医院_药学部药学部
通讯作者	Chen, Huiling
作者单位	1.School of Digital Media,Shenzhen Institute of Information Technology,Shenzhen,518172,China; 2.Wenzhou Mingcheng Construction Investment Group Co.,Ltd.,China; 3.College of Physics and Electronic Information Engineering,Wenzhou University,Wenzhou,325035,China; 4.Cancer Hospital Chinese Academy of Medical Sciences (Shenzhen Hospital),Shenzhen,518000,China; 5.Analytical and Testing Center,Wenzhou Medical University,Wenzhou,325000,China; 6.Department of Pharmacy,The First Affiliated Hospital of Wenzhou Medical University,Nanbaixiang Street, Ouhai District,Wenzhou City,325000,China
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.