Multiparameter Prediction Model for Atrial Fibrillation after CABG (CROSBI ID 518909)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Sovilj, Siniša ; Rajsman, Gordana ; Magjarević, Ratko ;
engleski
Multiparameter Prediction Model for Atrial Fibrillation after CABG
The aim of the study was to develop a multiparameter prediction model of Atrial Fibrillation (AF) after Coronary Artery Bypass Grafting (CABG) based on measured P wave parameters. We recorded the standard II lead ECG for at least 48 hours after surgery in 48 patients. In contrast to previous research and in order to enable the analysis of more data we decided to record the ECG continuously. The ECGs were processed offline and a vector of 82 P-wave parameters was calculated for every hour of the record. The segmentation of the ECGs was based on wavelet QRS and P-wave detectors. The calculated P-wave parameters were used for building classification and regression trees. We built several decision trees (models) for discriminating the AF prone patients after CABG. With the best tree model, we were able to achieve specificity (96.55%), sensitivity (54, 54%), positive predictivity (85.71%), negative predictivity (84.84 %), accuracy (85, 00%).
atrial fibrillation; CABG; wavelet transformation; p wave; classification tree; prediction model
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Podaci o prilogu
489-492-x.
2006.
objavljeno
Podaci o matičnoj publikaciji
Murray, Alan ;
Valencia: Institute of Electrical and Electronics Engineers (IEEE)
Podaci o skupu
Computers in Cardiology 2006
poster
17.09.2006-20.09.2006
Valencia, Španjolska