Intelligent Data Analysis for Knowledge Discovery, Patient Monitoring and Quality Assessment

被引:0
|
作者
Peek, N. [1 ]
Swift, S. [2 ]
机构
[1] Univ Amsterdam, Acad Med Ctr, Dept Med Informat, NL-1100 DE Amsterdam, Netherlands
[2] Brunel Univ, Sch Informat Syst Comp & Math, London, England
关键词
HIGH-RISK SUBGROUPS; HEALTH-CARE; MEDICAL DIAGNOSIS; ACUTE PHYSIOLOGY; SYSTEMS BIOLOGY; CASE-MIX; MORTALITY; CLASSIFICATION; IDENTIFICATION; PERFORMANCE;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Objective: To introduce the focus theme of Methods of Information in Medicine on Intelligent Data Analysis for Knowledge Discovery, Patient Monitoring and Quality Assessment. Methods: Based on two workshops on Intelligent Data Analysis in bioMedicine (IDAMAP) held in Washington, DC, USA (2010) and Bled, Slovenia (2011), six authors were invited to write full papers for the focus theme. Each paper was throughly reviewed by anonymous referees and revised one or more times by the authors. Results: The selected papers cover four ongoing and emerging topics in Intelligent Data Analysis (IDA), being i) systems biology and metabolic pathway modelling; ii) gene expression data modelling; iii) signal processing from in-home monitoring systems; and iv) quality of care assessment. Each of these topics is discussed in detail to introduce the papers to the reader. Conclusion: The development and application of IDA methods in biomedicine is an active area of research which continues to blend with other subfields of medical informatics. As data become increasingly ubiquitous in the biomedical domain, the demand for fast, smart and flexible data analysis methods is undiminished.
引用
收藏
页码:318 / 322
页数:5
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