Title :
A Hybrid Data Mining and Case-Based Reasoning User Modeling System (HDCU) for Monitoring and Predicting of Blood Sugar Level
Author :
Yuan, Chen Zhi ; Isa, Dino ; Blanchfield, Peter
Author_Institution :
Sch. of Comput. Sci., Univ. of Nottingham, Kuala Lumpur
Abstract :
In this paper we present HDCU, a hybrid data mining and case-based reasoning user modeling system, which is used to monitor and predict the blood sugar level in diabetics. The practical objective for this project is to reduce the cost of direct blood sugar self monitoring by minimizing the number of times that a diabetic needs to measure his or her sugar levels every day. From the technological point of view, the main aim is using the support vector machine as the classifier and implementing a case-based reasoning cycle as the retrieval cycle in order to indirectly determine and predict blood sugar level in diabetics and finally implement this software into a mobile device with wireless sensor networks and link it to a server which houses the relevant knowledgebase.
Keywords :
case-based reasoning; data mining; diagnostic expert systems; diseases; patient monitoring; support vector machines; user modelling; wireless sensor networks; blood sugar level monitoring; blood sugar level prediction; case-based reasoning user modeling system; data mining; diabetics; retrieval cycle; support vector machine; wireless sensor networks; Biomedical monitoring; Biosensors; Costs; Data mining; Diabetes; Network servers; Predictive models; Support vector machine classification; Support vector machines; Wireless sensor networks; blood sugar prediction; case-based reasoning; data mining; support vector machine;
Conference_Titel :
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-0-7695-3336-0
DOI :
10.1109/CSSE.2008.1095
