A Multinomial Logistic Regression Approach for Arrhythmia Detection

Behadada, Omar, Trovati, Marcello, Kontonatsios, Georgios and Korkontzelos, Yannis (2018) A Multinomial Logistic Regression Approach for Arrhythmia Detection. International Journal of Distributed Systems and Technologies (IJDST), 8 (4). pp. 17-33. ISSN 1947-3532

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Abstract

Cardiovascular diseases are the leading causes on mortality in the world. As a consequence, tools and methods providing useful and applicable insights into their assessment play a crucial role in the prediction and managements of specific heart conditions. In this article, we introduce a method based on multi-class Logistic Regression as a classifier to provide a powerful and accurate insight into cardiac arrhythmia, which is one of the predictors of serious vascular diseases. As suggested by our evaluation, this provides a robust, scalable, and accurate system, which can successfully tackle the challenges posed by the utilisation of big data in the medical sector.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Computing and Information Systems
Date Deposited: 01 Mar 2018 10:36
URI: http://repository.edgehill.ac.uk/id/eprint/10137

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