Logistic Regression Multinomial for Arrhythmia Detection

Research output: Contribution to conferencePaper

4 Citations (Scopus)
77 Downloads (Pure)

Abstract

In this paper, we introduce a method based on logistics Regression multi-class as a classifier to provide a powerful and accurate insight into cardiac arrhythmia. As suggested by our evaluation, this provide a robust, scalable, and accurate system, which can successfully tackle the challenges posed by the utilization of big data in the medical sector.
Original languageEnglish
Pages133-137
DOIs
Publication statusE-pub ahead of print - 19 Dec 2016
Event2nd International Workshop on Data-driven Self-regulating Systems - Augsburg, Germany
Duration: 12 Sep 2016 → …

Workshop

Workshop2nd International Workshop on Data-driven Self-regulating Systems
CountryGermany
CityAugsburg
Period12/09/16 → …

Keywords

  • Multinomial Logistic Regression
  • Knowledge Extraction
  • Big Data

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  • Cite this

    Behadada, O., Trovati, M., Chikh, MA., Bessis, N., & Korkontzelos, Y. (2016). Logistic Regression Multinomial for Arrhythmia Detection. 133-137. Paper presented at 2nd International Workshop on Data-driven Self-regulating Systems, Augsburg, Germany. https://doi.org/10.1109/FAS-W.2016.39