Data Analytic for Healthcare Cyber Physical System

被引:1
|
作者
Gan, Wensheng [1 ,2 ]
Hu, Kaixia [3 ]
Huang, Gengsen [3 ]
Chien, Wei-Che [4 ]
Chao, Han-Chieh [5 ,6 ]
Meng, Weizhi [7 ]
机构
[1] Jinan Univ, Coll Cyber Secur, Guangzhou 510632, Peoples R China
[2] Pazhou Lab, Guangzhou 510330, Peoples R China
[3] Jinan Univ, Coll Cyber Secur, Guangzhou 510632, Peoples R China
[4] Natl Dong Hwa Univ, Dept Comp Sci & Informat Engn, Hualien 97401, Taiwan
[5] Natl Dong Hwa Univ, Dept Elect Engn, Hualien 97401, Taiwan
[6] UCSI Univ, Inst Comp Sci & Innovat, Kuala Lumpur, Malaysia
[7] Tech Univ Denmark DTU, Dept Appl Math & Comp Sci, Cyber Secur Sect, DK-2800 Lyngby, Denmark
基金
中国国家自然科学基金;
关键词
Medical services; Data mining; Data analysis; Drugs; Decision making; Computer crime; Bioinformatics; Healthcare; CPS; medical data; data mining; contiguous sequence; MINING SEQUENTIAL PATTERNS;
D O I
10.1109/TNSE.2023.3278674
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Nowadays, a large number of AI-powered healthcare cyber-physical systems (CPSs) have been used in healthcare services. In order to provide better care, AI-powered healthcare CPSs analyze the data they collect using a variety of techniques. Data analysis for artificial intelligence (AI)-driven healthcare CPS is one of these approaches. However, none of the techniques in data analysis can provide a good representation of contiguous and negative information. Therefore, we are the first to introduce the problem of contiguous negative sequential pattern mining. A novel algorithm called Contiguous Negative Sequential Pattern Miner (CNSPM) is proposed to discover and analyze contiguous negative sequential patterns (CNSPs) from the data collected by healthcare CPSs. Finally, we select some real medical and non-medical datasets to conduct numerous experiments. We further analyze the discovered patterns and show how healthcare services can use meaningful patterns for medical decision-making. The performance results on these datasets demonstrate that the proposed algorithm can discover more valuable patterns efficiently and effectively from the collected and transformed medical data.
引用
收藏
页码:2490 / 2502
页数:13
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