Machine Learning Algorithms in Cardiology Domain: A Systematic Review

Q3 Computer Science

Open Bioinformatics Journal Pub Date : 2020-04-23 DOI:10.2174/1875036202013010025

Aleksei Dudchenko, Matthias Ganzinger, G. Kopanitsa

引用次数: 7

Abstract

For organizing this review, we adopted the PRISMA statement. We used PubMed as the search engine and identified the search keywords as “Machine Learning”, “Data Mining”, “Cardiology”, and “Cardiovascular” in combinations. Scientific articles and conference papers published between 2013-2017 reporting about implementations of ML algorithms in the domain of cardiology have been included in this review.

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心脏病学领域的机器学习算法:系统综述

为了组织这次审查，我们通过了PRISMA声明。我们使用PubMed作为搜索引擎，将搜索关键词确定为“机器学习”、“数据挖掘”、“心脏病学”和“心血管”组合。2013-2017年间发表的关于ML算法在心脏病学领域实现的科学文章和会议论文已被纳入本综述。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Open Bioinformatics Journal Computer Science-Computer Science (miscellaneous)

CiteScore

2.40

自引率

0.00%

发文量

期刊介绍： The Open Bioinformatics Journal is an Open Access online journal, which publishes research articles, reviews/mini-reviews, letters, clinical trial studies and guest edited single topic issues in all areas of bioinformatics and computational biology. The coverage includes biomedicine, focusing on large data acquisition, analysis and curation, computational and statistical methods for the modeling and analysis of biological data, and descriptions of new algorithms and databases. The Open Bioinformatics Journal, a peer reviewed journal, is an important and reliable source of current information on the developments in the field. The emphasis will be on publishing quality articles rapidly and freely available worldwide.