Decision Support Systems in Cardiology: A Systematic Review

被引：4
|
作者：
Dudchenko, Aleksey [1 ]
Kopanitsa, Georgy [1 ,2 ]
机构：
[1] Natl Res Tomsk Polytech Univ, Tomsk, Russia
[2] Tomsk State Univ Architecture & Bldg, Tomsk, Russia
来源：
PHEALTH 2017 | 2017年 / 237卷
关键词：
Heart disease; prediction and diagnosis systems; artificial intelligence; HEART; PERFORMANCE; DISEASE; RISK; PREDICTION; DIAGNOSIS; ALGORITHM;
D O I：
10.3233/978-1-61499-761-0-209
中图分类号：
R-058 [];
学科分类号：
摘要：
The aim of this work was to identify the most common approaches used in the intelligent decision support systems employed in the diagnosis of cardiovascular diseases and identify accuracy of these systems. Forty-one relevant publications were included in the review using Scopus and Web of Science. Knowledge base and fuzzy logic and ANN is the most commonly used approach to diagnosis and prediction. The accuracy of the considered systems reaches 98%.
引用
收藏
页码：209 / 214
页数：6
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