AIMC Topic: Cardiac Conduction System Disease

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Use of machine learning to classify high-risk variants of uncertain significance in lamin A/C cardiac disease.

Heart rhythm Dec 24, 2021
BACKGROUND: Variation in lamin A/C results in a spectrum of clinical disease, including arrhythmias and cardiomyopathy. Benign variation is rare, and classification of LMNA missense variants via in silico prediction tools results in a high rate of va...
Humans Machine Learning Heart Diseases Pedigree Cardiac Conduction System Disease Lamin Type A
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Cardiac arrhythmia detection using deep learning: A review.

Journal of electrocardiology Aug 8, 2019
Due to its simplicity and low cost, analyzing an electrocardiogram (ECG) is the most common technique for detecting cardiac arrhythmia. The massive amount of ECG data collected every day, in home and hospital, may preclude data review by human operat...
Humans Machine Learning Deep Learning Electrocardiography Arrhythmias, Cardiac Cardiac Conduction System Disease
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Multiclass Classification of Cardiac Arrhythmia Using Improved Feature Selection and SVM Invariants.

Computational and mathematical methods in medicine Mar 5, 2018
Arrhythmia is considered a life-threatening disease causing serious health issues in patients, when left untreated. An early diagnosis of arrhythmias would be helpful in saving lives. This study is conducted to classify patients into one of the sixte...
Humans Support Vector Machine Arrhythmias, Cardiac Datasets as Topic Cardiac Conduction System Disease
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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...
Humans Neural Networks, Computer Arrhythmias, Cardiac Cardiac Conduction System Disease
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