Machine learning based hybrid anomaly detection technique for automatic diagnosis of cardiovascular diseases using cardiac sympathetic nerve activity and electrocardiogram - Terzi, Merve Begum; Arikan, Orhan (Biomedizinische Technik, 2024)
Keywords: Anomalies; Artificial intelligence; Artificial neural networks; Automation; Broadband; Cardiovascular diseases; classification; Clustering; Coronary artery disease; Data processing; Decision support systems; Deep learning; Diagnosis; Diagnostic systems; EKG; Electrocardiography; Feature extraction; Heart diseases; Learning algorithms; Machine learning; Nerves; Neural networks; Neyman-Pearson hypothesis testing; Outliers (statistics); Probabilistic models; Signal processing; Statistical analysis; Sympathetic nerves; synthetic minority oversampling technique (SMOTE); Time domain analysis; Unsupervised learning; clustering; classification; Neyman-Pearson hypothesis testing; feature extraction; signal processing; synthetic minority oversampling technique (SMOTE)