Browsing by Keywords "Atrial fibrillation"
Now showing items 1-6 of 6
-
Application of the RIMARC algorithm to a large data set of action potentials and clinical parameters for risk prediction of atrial fibrillation
(Springer, 2015)Ex vivo recorded action potentials (APs) in human right atrial tissue from patients in sinus rhythm (SR) or atrial fibrillation (AF) display a characteristic spike-and-dome or triangular shape, respectively, but variability ... -
Data mining experiments on the Angiotensin II-Antagonist in Paroxysmal Atrial Fibrillation (ANTIPAF-AFNET 2) trial: ‘exposing the invisible’
(Oxford University Press, 2016)Aims: The aims of this study include (i) pursuing data-mining experiments on the Angiotensin II-Antagonist in Paroxysmal Atrial Fibrillation (ANTIPAF-AFNET 2) trial dataset containing atrial fibrillation (AF) burden scores ... -
Demographics, treatment and outcomes of atrial fibrillation in a developing country: the population-based TuRkish Atrial Fibrillation (TRAF) cohort
(Oxford University Press, 2017)Aims: Although atrial fibrillation (AF) is increasingly common in developed countries, there is limited information regarding its demographics, co-morbidities, treatments and outcomes in the developing countries. We present ... -
Ischemic stroke phenotype in patients with nonsustained atrial fibrillation
(Lippincott Williams and Wilkins, 2015)Background and Purpose: The widespread use of ambulatory cardiac monitoring has not only increased the detection of high-risk arrhythmias like persistent and paroxysmal atrial fibrillation (AF), but also made it possible ... -
Predictors of sinus rhythm after electrical cardioversion of atrial fibrillation: results from a data mining project on the Flec-SL trial data set
(Oxford University Press, 2017)Data mining is the computational process to obtain information from a data set and transform it for further use. Herein, through data mining with supportive statistical analyses, we identified and consolidated variables ... -
A window-based time series feature extraction method
(Elsevier, 2017)This study proposes a robust similarity score-based time series feature extraction method that is termed as Window-based Time series Feature ExtraCtion (WTC). Specifically, WTC generates domain-interpretable results and ...