Morphological and Temporal ECG Features for Myocardial Infarction Detection Using Support Vector Machines
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Publisher
Springer International Publishing
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http://link.springer.com/content/pdf/10.1007/978-3-030-30648-9_24
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4. Hernández, A.I., Dumont, J., Altuve, M., Beuchée, A., Carrault, G.: Evolutionary optimization of ECG feature extraction methods: applications to the monitoring of adult myocardial ischemia and neonatal apnea bradycardia events. In: Gacek, A., Pedrycz, W. (eds.) ECG Signal Processing, Classification and Interpretation: A Comprehensive Framework of Computational Intelligence, pp. 237–273. Springer, London (2012)
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1. Exploring Machine Learning Algorithms for Myocardial Infarction Diagnosis;2024 International Conference on Intelligent Systems and Computer Vision (ISCV);2024-05-08
2. Linear and Nonlinear Features for Myocardial Infarction Detection Using Support Vector Machine on 12-Lead ECG Recordings;8th European Medical and Biological Engineering Conference;2020-11-30
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