Zhang Yang, Fong Simon, Fiaidhi Jinan, Mohammed Sabah
Department of Computer and Information Science, University of Macau, Macau.
J Biomed Biotechnol. 2012;2012:580186. doi: 10.1155/2012/580186. Epub 2012 Jul 18.
This research aims to describe a new design of data stream mining system that can analyze medical data stream and make real-time prediction. The motivation of the research is due to a growing concern of combining software technology and medical functions for the development of software application that can be used in medical field of chronic disease prognosis and diagnosis, children healthcare, diabetes diagnosis, and so forth. Most of the existing software technologies are case-based data mining systems. They only can analyze finite and structured data set and can only work well in their early years and can hardly meet today's medical requirement. In this paper, we describe a clinical-support-system based data stream mining technology; the design has taken into account all the shortcomings of the existing clinical support systems.
本研究旨在描述一种新型数据流挖掘系统的设计,该系统能够分析医疗数据流并进行实时预测。开展这项研究的动机源于人们日益关注将软件技术与医疗功能相结合,以开发可用于慢性病预后与诊断、儿童医疗保健、糖尿病诊断等医疗领域的软件应用程序。现有的大多数软件技术都是基于案例的数据挖掘系统。它们只能分析有限的结构化数据集,并且仅在早期能够良好运行,难以满足当今的医疗需求。在本文中,我们描述了一种基于临床支持系统的数据流挖掘技术;该设计考虑到了现有临床支持系统的所有缺点。