AIMC Topic: Electrocardiography

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Artificial intelligence capable of detecting left ventricular hypertrophy: pushing the limits of the electrocardiogram?

Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology Mar 1, 2020
Artificial Intelligence Echocardiography Electrocardiography Hypertrophy, Left Ventricular Humans
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Comparing the performance of artificial intelligence and conventional diagnosis criteria for detecting left ventricular hypertrophy using electrocardiography.

Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology Mar 1, 2020
AIMS: Although left ventricular hypertrophy (LVH) has a high incidence and clinical importance, the conventional diagnosis criteria for detecting LVH using electrocardiography (ECG) has not been satisfied. We aimed to develop an artificial intelligen...
Electrocardiography Hypertrophy, Left Ventricular Retrospective Studies Echocardiography Humans Artificial Intelligence
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[Detection of inferior myocardial infarction based on densely connected convolutional neural network].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Feb 25, 2020
Inferior myocardial infarction is an acute ischemic heart disease with high mortality, which is easy to induce life-threatening complications such as arrhythmia, heart failure and cardiogenic shock. Therefore, it is of great clinical value to carry o...
Electrocardiography Inferior Wall Myocardial Infarction Neural Networks, Computer Sensitivity and Specificity Humans
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Detection of Hypertrophic Cardiomyopathy Using a Convolutional Neural Network-Enabled Electrocardiogram.

Journal of the American College of Cardiology Feb 25, 2020
BACKGROUND: Hypertrophic cardiomyopathy (HCM) is an uncommon but important cause of sudden cardiac death.
Humans Aged Adult Male Neural Networks, Computer Algorithms Female Cardiomyopathy, Hypertrophic Middle Aged Models, Cardiovascular Electrocardiography
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[Automatic Identification and Classification Diagnosis of Atrial Ventricular Hypertrophy Electrocardiogram Based on Convolutional Neural Network].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation Jan 8, 2020
OBJECTIVE: Identifying Atrial Ventricular Hypertrophy Electrocardiogram (AVH ECG)and diagnosing the classification of theirs automatically.
Electrocardiography Hypertrophy Heart Atria Neural Networks, Computer China Humans
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Contribution of neural networks in the diagnosis and treatment of cardiac arrhythmia.

Discovery medicine Jan 1, 2020
Arrhythmia is a dangerous disease in which the heart rhythm varies and it may be very fast or very slow. Rapid heartbeats can lead to shortness of breath, chest pain, and sudden weakness, whereas slow heartbeats can lead to dizziness, problems with c...
Humans Treatment Outcome Diagnosis, Computer-Assisted Anti-Arrhythmia Agents Deep Learning Arrhythmias, Cardiac Electrocardiography
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Assessment of mental workload based on multi-physiological signals.

Technology and health care : official journal of the European Society for Engineering and Medicine Jan 1, 2020
BACKGROUND: Mental workload is one of the contributing factors to human errors in road accidents or other potentially adverse incidents.
Support Vector Machine Humans Task Performance and Analysis Electroencephalography Male Workload Young Adult Mental Fatigue Reaction Time Electrocardiography Adult Attention Image Interpretation, Computer-Assisted
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High-Throughput, Contact-Free Detection of Atrial Fibrillation From Video With Deep Learning.

JAMA cardiology Jan 1, 2020
This study uses video and a pretrained deep convolutional neural network to analyze facial photoplethysmographic signals in detection of atrial fibrillation.
Face Proof of Concept Study Humans Neural Networks, Computer Deep Learning Male Female Predictive Value of Tests Photoplethysmography Middle Aged Reproducibility of Results Aged, 80 and over Electrocardiography Atrial Fibrillation Case-Control Studies Adult Video Recording Aged
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The electrocardiogram endeavour: from the Holter single-lead recordings to multilead wearable devices supported by computational machine learning algorithms.

Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology Jan 1, 2020
This review aims to provide a comprehensive recapitulation of the evolution in the field of cardiac rhythm monitoring, shedding light in recent progress made in multilead ECG systems and wearable devices, with emphasis on the promising role of the ar...
Algorithms Wearable Electronic Devices Electrocardiography Signal Processing, Computer-Assisted Humans Artificial Intelligence Machine Learning
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[Heartbeat-based end-to-end classification of arrhythmias].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University Sep 30, 2019
OBJECTIVE: We propose a heartbeat-based end-to-end classification of arrhythmias to improve the classification performance for supraventricular ectopic beat (SVEB) and ventricular ectopic beat (VEB).
Heart Rate Algorithms Humans Ventricular Premature Complexes Electrocardiography Neural Networks, Computer Arrhythmias, Cardiac
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