title: Evaluation of stream mining classifiers for real-time clinical decision support system: a case study of blood glucose prediction in diabetes therapy.
abstract: Earlier on, a conceptual design on the real-time clinical decision support system (rt-CDSS) with data stream mining was proposed and published. The new system is introduced that can analyze medical data streams and can make real-time prediction. This system is based on a stream mining algorithm called VFDT. The VFDT is extended with the capability of using pointers to allow the decision tree to remember the mapping relationship between leaf nodes and the history records. In this paper, which is a sequel to the rt-CDSS design, several popular machine learning algorithms are investigated for their suitability to be a candidate in the implementation of classifier at the rt-CDSS. A classifier essentially needs to accurately map the events inputted to the system into one of the several predefined classes of assessments, such that the rt-CDSS can follow up with the prescribed remedies being recommended to the clinicians. For a real-time system like rt-CDSS, the major technological challenges lie in the capability of the classifier to process, analyze and classify the dynamic input data, quickly and upmost reliably. An experimental comparison is conducted. This paper contributes to the insight of choosing and embedding a stream mining classifier into rt-CDSS with a case study of diabetes therapy.
authors.affiliation: Department of Computer and Information Science, University of Macau, Macau, China.
authors.forename: Simon
authors.initials: S
authors.lastname: Fong
authors.forename: Yang
authors.initials: Y
authors.lastname: Zhang
authors.forename: Jinan
authors.initials: J
authors.lastname: Fiaidhi
authors.forename: Osama
authors.initials: O
authors.lastname: Mohammed
authors.forename: Sabah
authors.initials: S
authors.lastname: Mohammed
mesh_terms: D000465:Algorithms; D019540:Area Under Curve; D001499:Bayes Theorem; D001786:Blood Glucose / Q000032:analysis*; D003199:Computer Systems; D020000:Decision Support Systems, Clinical; D003920:Diabetes Mellitus / Q000097:blood* / Q000628:therapy*; D006801:Humans; D012372:ROC Curve
chemical_list: D001786:Blood Glucose