Results 321 to 330 of about 1,611,491 (358)

Ischemic heart disease and cardiac arrhythmia are associated with increased cardiac aging

Salih A, Rauseo E, Galazzo I, Pujadas ER, Campello V, Lekadir K, Aung N, Slabaugh G, Dabbagh G, Chahal A, Menegaz G, Petersen S.   +11 more
europepmc   +1 more source

An autosomal dominant cardiac arrhythmia syndrome, ST Depression Syndrome, is caused by thede novocreation of a cardiomyocyte enhancer

de Villiers CP, Downes DJ, Goel A, Pagnamenta AT, Ormondroyd E, Sparrow AJ, Nornes S, Giacopuzzi E, Rath P, Davies B, Schwessinger R, Gosden ME, Beagrie RA, Parkes D, Hastings R, Lise S, Salatino S, Roberts H, Lopopolo M, Weldon C, Trebes A, The WGS500 consortium, Buck D, Taylor JC, Redwood C, Rowland E, Tharmaratnam D, Stuart G, Lambiase PD, De Val S, Hughes JR, Watkins H.   +31 more
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

A 13.34 μW Event-Driven Patient-Specific ANN Cardiac Arrhythmia Classifier for Wearable ECG Sensors

IEEE Transactions on Biomedical Circuits and Systems, 2019
Artificial neural network (ANN) and its variants are favored algorithm in designing cardiac arrhythmia classifier (CAC) for its high accuracy. However, the implementation of ultralow power ANN-CAC is challenging due to the intensive computations ...
Yang Zhao, Zhongxia Shang, Y. Lian
semanticscholar   +1 more source

Combining deep neural networks and engineered features for cardiac arrhythmia detection from ECG recordings

Physiological Measurement, 2019
Objective: We aim to combine deep neural networks and engineered features (hand-crafted features based on medical domain knowledge) for cardiac arrhythmia detection from short single-lead ECG recordings.
linda Qiao, Yuxi Zhou, Meng Wu, Junyuan Shang, Qingyun Wang, Hongyan Li, Junqing Xie   +6 more
semanticscholar   +1 more source

Classification of Cardiac Arrhythmia of 12 Lead ECG Using Combination of SMOTEENN, XGBoost and Machine Learning Algorithms

International Symposium on Embedded Computing and System Design, 2019
Cardiac Arrhythmia is one of those common diseases leading to severe health problems for patients and even sudden death in some cases. Early detection of arrhythmias has a great role in saving lives which can be achieved by analyzing and classifying ECG ...
B R Manju, Anju R Nair
semanticscholar   +1 more source

A new transfer learning approach to detect cardiac arrhythmia from ECG signals

Signal, Image and Video Processing, 2022
Mohebbanaaz, L. Kumar, Y. Sai
semanticscholar   +1 more source

A Wearable Auto-Patient Adaptive ECG Processor for Shockable Cardiac Arrhythmia

International Symposium on Security in Computing and Communications, 2018
A non-machine learning patient-specific shockable cardiac arrhythmia (SCA) classification processor based on single lead electrocardiogram (ECG) is presented. The proposed SCA detection processor integrates a hardware-efficient reduced-set-of-five (RSF5)
S. Abubakar, Muhammad Rizwan Khan, Wala Saadeh, Muhammad Awais Bin Altaf   +3 more
semanticscholar   +1 more source

Prediction and Classification of Cardiac Arrhythmia

Advances in Intelligent Systems and Computing, 2021
Aashuli Gupta, Arnob Banerjee, Disha Babaria, Kunal Lotlikar, Hema Raut   +4 more
semanticscholar   +1 more source

A framework for cardiac arrhythmia detection from IoT-based ECGs

World wide web (Bussum), 2020
Jinyuan He, Jia Rong, Le Sun, Hua Wang, Yanchun Zhang, Jiangang Ma   +5 more
semanticscholar   +1 more source