Research Article
A Support Vector Machine Approach for Categorization of Patients Suffering from Chronic Diseases
@INPROCEEDINGS{10.1007/978-3-642-29734-2_36, author={Christos Bellos and Athanasios Papadopoulos and Roberto Rosso and Dimitrios Fotiadis}, title={A Support Vector Machine Approach for Categorization of Patients Suffering from Chronic Diseases}, proceedings={Wireless Mobile Communication and Healthcare. Second International ICST Conference, MobiHealth 2011, Kos Island, Greece, October 5-7, 2011. Revised Selected Papers}, proceedings_a={MOBIHEALTH}, year={2012}, month={10}, keywords={Personalized treatment Wearable Monitoring Management of Chronic Diseases Real-time classification}, doi={10.1007/978-3-642-29734-2_36} }- Christos Bellos
Athanasios Papadopoulos
Roberto Rosso
Dimitrios Fotiadis
Year: 2012
A Support Vector Machine Approach for Categorization of Patients Suffering from Chronic Diseases
MOBIHEALTH
Springer
DOI: 10.1007/978-3-642-29734-2_36
Abstract
The CHRONIOUS system is an open-architecture integrated platform aiming at the management of chronic disease patients. The system consists of a body sensor network collecting patient’s vital signals, a Personal Digital Assistance (PDA) for the real-time data analysis based on a Decision Support System (DSS) and a central system for the deeper analysis of patient’s status and data storing. The DSS combines several data sources to decide upon the severity of patient’s current health status. The first pilot study has been designed and carried out using patients suffering from Chronic Obstructive Pulmonary Disease(COPD). The DSS facilitates a one-against-all multi-class Support Vector Machine (SVM) classification system. The performance of the categorization scheme provides high classification results for most of the patient’s health status levels. The involvement of a larger number of patients might increase further the performance of the system.
