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Heterogeneous data fusion and intelligent techniques embedded in a mobile application for real-time chronic disease
Christos Bellos1, Athanassios Papadopoulos, Roberto Rosso
1FORTH BRI Foundation for Research and Technology - Hellas, Biomedical Research, Ioannina, Greece. cbellos@cc.uoi.gr
Abstract:
CHRONIOUS system is an integrated platform aiming at the management of chronic disease patients. One of the most important components of the system is a Decision Support System (DSS) that has been developed in a Smart Device (SD). This component decides on patient's current health status by combining several data, which are acquired either by wearable sensors or manually inputted by the patient or retrieved from the specific database. In case no abnormal situation has been tracked, the DSS takes no action and remains deactivated until next abnormal situation pack of data are being acquired or next scheduled data being transmitted. The DSS that has been implemented is an integrated classification system with two parallel classifiers, combining an expert system (rule-based system) and a supervised classifier, such as Support Vector Machines (SVM), Random Forests, artificial Neural Networks (aNN like the Multi-Layer Perceptron), Decision Trees and Naïve Bayes. The above categorized system is useful for providing critical information about the health status of the patient.
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