Research Unit Human-Computer Interaction (HCI4MED), Institute for Medical Informatics, Statistics and Documentation, Medical University Graz, Auenbruggerplatz 2/V, Graz 8036, Austria.
BMC Bioinformatics. 2013 Jun 13;14:191. doi: 10.1186/1471-2105-14-191.
Professionals in the biomedical domain are confronted with an increasing mass of data. Developing methods to assist professional end users in the field of Knowledge Discovery to identify, extract, visualize and understand useful information from these huge amounts of data is a huge challenge. However, there are so many diverse methods and methodologies available, that for biomedical researchers who are inexperienced in the use of even relatively popular knowledge discovery methods, it can be very difficult to select the most appropriate method for their particular research problem.
A web application, called KNODWAT (KNOwledge Discovery With Advanced Techniques) has been developed, using Java on Spring framework 3.1. and following a user-centered approach. The software runs on Java 1.6 and above and requires a web server such as Apache Tomcat and a database server such as the MySQL Server. For frontend functionality and styling, Twitter Bootstrap was used as well as jQuery for interactive user interface operations.
The framework presented is user-centric, highly extensible and flexible. Since it enables methods for testing using existing data to assess suitability and performance, it is especially suitable for inexperienced biomedical researchers, new to the field of knowledge discovery and data mining. For testing purposes two algorithms, CART and C4.5 were implemented using the WEKA data mining framework.
生物医学领域的专业人员面临着越来越多的数据。开发方法来帮助知识发现领域的专业最终用户识别、提取、可视化和理解这些大量数据中的有用信息是一个巨大的挑战。然而,有如此多不同的方法和方法论可用,对于那些在使用甚至相对流行的知识发现方法方面没有经验的生物医学研究人员来说,选择最适合其特定研究问题的方法可能非常困难。
已经开发了一种名为 KNODWAT(使用高级技术进行知识发现)的 Web 应用程序,该应用程序使用 Java 上的 Spring 框架 3.1 并采用以用户为中心的方法。该软件在 Java 1.6 及更高版本上运行,需要一个 Web 服务器,如 Apache Tomcat,和一个数据库服务器,如 MySQL Server。对于前端功能和样式,使用了 Twitter Bootstrap 以及用于交互用户界面操作的 jQuery。
所提出的框架以用户为中心,高度可扩展和灵活。由于它允许使用现有数据进行测试的方法来评估适用性和性能,因此特别适合生物医学研究人员,他们是该领域的新手知识发现和数据挖掘。出于测试目的,使用 WEKA 数据挖掘框架实现了两个算法,CART 和 C4.5。