Title :
Adverse event prediction in patients with left ventricular assist devices
Author :
Tsipouras, M.G. ; Karvounis, E.C. ; Tzallas, A.T. ; Katertsidis, Nikolaos S. ; Goletsis, Yorgos ; Frigerio, Marco ; Verde, Alessandro ; Trivella, M.G. ; Fotiadis, Dimitrios I.
Author_Institution :
Biomed. Res. Inst., FORTH, Ioannina, Greece
Abstract :
This work presents the Treatment Tool, which is a component of the Specialist´s Decision Support Framework (SDSS) of the SensorART platform. The SensorART platform focuses on the management of heart failure (HF) patients, which are treated with implantable, left ventricular assist devices (LVADs). SDSS supports the specialists on various decisions regarding patients with LVADs including decisions on the best treatment strategy, suggestion of the most appropriate candidates for LVAD weaning, configuration of the pump speed settings, while also provides data analysis tools for new knowledge extraction. The Treatment Tool is a web-based component and its functionality includes the calculation of several acknowledged risk scores along with the adverse events appearance prediction for treatment assessment.
Keywords :
Web services; cardiology; data analysis; decision support systems; knowledge acquisition; medical computing; medical disorders; patient treatment; prosthetics; LVAD weaning; SDSS; SensorART platform; Specialist´s Decision Support Framework; Treatment Tool; acknowledged risk scores; adverse event appearance prediction; data analysis tool; heart failure patient management; implantable device; knowledge extraction; left ventricular assist device; pump speed setting configuration; treatment assessment; treatment strategy; web-based component; Data mining; Heart; Medical treatment; Niobium; Predictive models; Radio frequency; Support vector machines;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE
Conference_Location :
Osaka
DOI :
10.1109/EMBC.2013.6609750
