Application of the RIMARC algorithm to a large data set of action potentials and clinical parameters for risk prediction of atrial fibrillation

@article{Ravens2014ApplicationOT,
  title={Application of the RIMARC algorithm to a large data set of action potentials and clinical parameters for risk prediction of atrial fibrillation},
  author={Ursula Ravens and Deniz Katircioglu-{\"O}zt{\"u}rk and Erich Wettwer and Torsten Christ and Dobromir Dobrev and Niels Voigt and Claire Poulet and Simone Loose and Jana Simon and Agnes Stein and Klaus Matschke and Michael Knaut and Emre Oto and Ali Oto and H. Altay G{\"u}venir},
  journal={Medical & Biological Engineering & Computing},
  year={2014},
  volume={53},
  pages={263-273}
}
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 is huge within each rhythm group. The aim of our study was to apply the machine-learning algorithm ranking instances by maximizing the area under the ROC curve (RIMARC) to a large data set of 480 APs combined with retrospectively collected general clinical parameters and to… CONTINUE READING
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