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Follow-Up and Risk Assessment in Patients with Myocardial Infarction Using Artificial Neural Networks
Joint Authors
Zdravkovic, Marija
Milovanovic, Branislav
Gligorijević, Tatjana
Ševarac, Zoran
Đajić, Vlado
Hinić, Saša
Arsić, Marina
Aleksić, Milica
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-09-17
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Artificial neural networks (ANNs) are machine learning technique, inspired by the principles found in biological neurons.
This technique has been used for prediction and classification problems in many areas of medical signal processing.
The aim of this paper was to identify individuals with high risk of death after acute myocardial infarction using ANN.
A training dataset for ANN was 1705 consecutive patients who underwent 24-hour ECG monitoring, short ECG analysis, noninvasive beat-to-beat heart-rate variability, and baroreflex sensitivity that were followed for 3 years.
The proposed neural network classifier showed good performance for survival prediction: 88% accuracy, 81% sensitivity, 93% specificity, 0.85 F-measure, and area under the curve value of 0.77.
These findings support the theory that patients with high sympathetic activity (reduced baroreflex sensitivity) have an increased risk of mortality independent of other risk factors and that artificial neural networks can indicate the individuals with a higher risk.
American Psychological Association (APA)
Gligorijević, Tatjana& Ševarac, Zoran& Milovanovic, Branislav& Đajić, Vlado& Zdravkovic, Marija& Hinić, Saša…[et al.]. 2017. Follow-Up and Risk Assessment in Patients with Myocardial Infarction Using Artificial Neural Networks. Complexity،Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1143596
Modern Language Association (MLA)
Gligorijević, Tatjana…[et al.]. Follow-Up and Risk Assessment in Patients with Myocardial Infarction Using Artificial Neural Networks. Complexity No. 2017 (2017), pp.1-8.
https://search.emarefa.net/detail/BIM-1143596
American Medical Association (AMA)
Gligorijević, Tatjana& Ševarac, Zoran& Milovanovic, Branislav& Đajić, Vlado& Zdravkovic, Marija& Hinić, Saša…[et al.]. Follow-Up and Risk Assessment in Patients with Myocardial Infarction Using Artificial Neural Networks. Complexity. 2017. Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1143596
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1143596