AIMC Topic: Arrhythmias, Cardiac

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Development and Validation of a Deep-Learning Model to Screen for Hyperkalemia From the Electrocardiogram.

JAMA cardiology May 1, 2019
IMPORTANCE: For patients with chronic kidney disease (CKD), hyperkalemia is common, associated with fatal arrhythmias, and often asymptomatic, while guideline-directed monitoring of serum potassium is underused. A deep-learning model that enables non...
Male Humans Middle Aged Neural Networks, Computer Prevalence Aged Artificial Intelligence Mass Screening Aged, 80 and over Arrhythmias, Cardiac Algorithms Sensitivity and Specificity Hyperkalemia Retrospective Studies Female Deep Learning Electrocardiography Renal Insufficiency, Chronic
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[Deep residual convolutional neural network for recognition of electrocardiogram signal arrhythmias].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Apr 25, 2019
Electrocardiogram (ECG) signals are easily disturbed by internal and external noise, and its morphological characteristics show significant variations for different patients. Even for the same patient, its characteristics are variable under different...
Humans Neural Networks, Computer Electrocardiography Algorithms Arrhythmias, Cardiac Heart Rate Sensitivity and Specificity
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[Automatic Identifcation of Heart Block Precise Location Based on Sparse Connection Residual Network].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation Mar 30, 2019
OBJECTIVE: To classify Right Bundle Branch Block (RBBB),Left Bundle Branch Block (LBBB) and normal ECG signals automatically.
Humans Neural Networks, Computer Bundle-Branch Block Algorithms Electrocardiography Arrhythmias, Cardiac
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[A DenseNet-based diagnosis algorithm for automated diagnosis using clinical ECG data].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University Jan 30, 2019
OBJECTIVE: To train convolutional networks using multi-lead ECG data and classify new data accurately to provide reliable information for clinical diagnosis.
Algorithms Sensitivity and Specificity Electrocardiography Arrhythmias, Cardiac Databases as Topic Humans Neural Networks, Computer
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Artificial intelligence for the electrocardiogram.

Nature medicine Jan 1, 2019
Cardiologists Artificial Intelligence Electrocardiography Arrhythmias, Cardiac Humans
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QRS Detection and Measurement Method of ECG Paper Based on Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
In this paper, we propose an end-to-end approach to addressing QRS complex detection and measurement of Electrocardiograph (ECG) paper using convolutional neural networks (CNNs). Unlike conventional detection solutions that convert images to digital ...
Neural Networks, Computer Algorithms Databases, Factual Electrocardiography Arrhythmias, Cardiac Humans
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Real-Time Cardiac Arrhythmia Classification Using Memristor Neuromorphic Computing System.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
Cardiac arrhythmia is known to be one of the most common causes of death worldwide. Therefore, development of efficient arrhythmia detection techniques is essential to save patients' lives. In this paper, we introduce a new real-time cardiac arrhythm...
Cardiac Conduction System Disease Neural Networks, Computer Arrhythmias, Cardiac Humans
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Design of a hybrid model for cardiac arrhythmia classification based on Daubechies wavelet transform.

Advances in clinical and experimental medicine : official organ Wroclaw Medical University Jun 1, 2018
BACKGROUND: Automation in cardiac arrhythmia classification helps medical professionals make accurate decisions about the patient's health.
Humans Algorithms Arrhythmias, Cardiac Diagnosis, Computer-Assisted Wavelet Analysis Electrocardiography Support Vector Machine
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[Design and Implementation of Portable Abnormal ECG Signal Analysis Instrument Based on Feature Classifcation].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation Feb 8, 2018
OBJECTIVES: To collect and analyze the ECG signal in real time, the analog filter and the signal amplifier were used to construct the abnormal signal acquisition and classification system.
Support Vector Machine Signal Processing, Computer-Assisted Heart Arrhythmias, Cardiac Humans Algorithms Electrocardiography
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Machine-Learning Prediction of Drug-Induced Cardiac Arrhythmia: Analysis of Gene Expression and Clustering.

Critical reviews in biomedical engineering Jan 1, 2018
A marked delay in the electrical repolarization of heart ventricles is characterized by prolongation of the Q-T wave (QT) interval on a surface electrocardiogram. Such a delay can lead to potentially life-threatening cardiac arrhythmia (torsades de p...
False Positive Reactions Cluster Analysis Torsades de Pointes Signal Processing, Computer-Assisted Heart MAP Kinase Signaling System Female Animals Humans Drug Evaluation, Preclinical Electrocardiography Gene Expression Regulation Reproducibility of Results Machine Learning Gene Expression Profiling Male Clinical Trials as Topic Heart Ventricles Support Vector Machine Sensitivity and Specificity Mice Drug Design Arrhythmias, Cardiac Rats
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