Publications citing AF Classification from a Short Single Lead ECG Recording: The PhysioNet/Computing in Cardiology Challenge 2017 v1.0.0

A convolutional neural network for ECG annotation as the basis for classification of cardiac rhythms
Philipp Sodmann, Marcus Vollmer, Neetika Nath et al. Physiological Measurement, 2018. Cites: paper

Automatic Detection of Atrial Fibrillation and Other Arrhythmias in ECG Recordings Acquired by a Smartphone Device
Lucia Billeci, Magda Costi, David Lombardi et al. Electronics, 2018. Cites: paper

Cardiac anomaly detection based on time and frequency domain features using tree-based classifiers
Martin Kropf, Dieter Hayn, Daniel Armando Morris et al. Physiological Measurement, 2018. Cites: paper

Classification of short single-lead electrocardiograms (ECGs) for atrial fibrillation detection using piecewise linear spline and XGBoost
Yao Chen, Xiao Wang, Yonghan Jung et al. Physiological Measurement, 2018. Cites: paper

Dynamic signal quality index for electrocardiograms
Negin Yaghmaie, Mohammad Ali Maddah-Ali, Herbert F Jelinek et al. Physiological Measurement, 2018. Cites: paper

An SVM approach for identifying atrial fibrillation
Вадим Глинер, Yael Yaniv. Physiological Measurement, 2018. Cites: paper

Cardiac Arrhythmia Detection from Single-lead ECG using CNN and LSTM assisted by Oversampling
Dhwaj Verma, Sonali Agarwal. International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2018. Cites: paper

Detection of atrial fibrillation from ECG recordings using decision tree ensemble with multi-level features
Minggang Shao, Guangyu Bin, Shuicai Wu et al. Physiological Measurement, 2018. Cites: paper

SPECTRO-TEMPORAL ECG ANALYSIS FOR ATRIAL FIBRILLATION DETECTION
Zheng Ming Zhao, Simo Särkkä, Ali Bahrami Rad. Machine learning for signal processing ..., 2018. Cites: paper

Identifying the mislabeled training samples of ECG signals using machine learning
Yaoguang Li, Wei Cui. Biomedical Signal Processing and Control, 2018. Cites: paper

ECG signal classification for the detection of cardiac arrhythmias using a convolutional recurrent neural network
Zhaohan Xiong, Martyn Peter Nash, Elizabeth C. Cheng et al. Physiological Measurement, 2018. Cites: paper

Multi-stage SVM approach for cardiac arrhythmias detection in short single-lead ECG recorded by a wearable device
Radovan Smíšek, Jakub Hejč, Marina Ronzhina et al. Physiological Measurement, 2018. Cites: paper

Parallel use of a convolutional neural network and bagged tree ensemble for the classification of Holter ECG
Filip Plešinger, Petr Nejedlý, Ivo Viščor et al. Physiological Measurement, 2018. Cites: paper

Ranking of the most reliable beat morphology and heart rate variability features for the detection of atrial fibrillation in short single-lead ECG
Ivaylo Ivanov Christov, Vessela Krasteva, Iana Ivaylova Simova et al. Physiological Measurement, 2018. Cites: paper

Densely connected convolutional networks for detection of atrial fibrillation from short single-lead ECG recordings
Jonathan Rubin, Saman Parvaneh, Asif Rahman et al. Journal of Electrocardiology, 2018. Cites: paper

Analyzing single-lead short ECG recordings using dense convolutional neural networks and feature-based post-processing to detect atrial fibrillation
Saman Parvaneh, Jonathan Rubin, Asif Rahman et al. Physiological Measurement, 2018. Cites: paper

A Simple Probabilistic Model for Uncertainty Estimation
Kuvaev Alexander, Roman Khudorozhkov. arXiv (Cornell University), 2018. Cites: paper

Detection of Paroxysmal Atrial Fibrillation using Attention-based Bidirectional Recurrent Neural Networks
Supreeth Prajwal Shashikumar, Amit Jasvant Shah, Gari D. Clifford et al. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2018. Cites: paper

Ensembling convolutional and long short-term memory networks for electrocardiogram arrhythmia detection
Philip A. Warrick, Masun Nabhan Homsi. Physiological Measurement, 2018. Cites: paper

A Novel Atrial Fibrillation Prediction Algorithm Applicable to Recordings from Portable Devices
Zhi Li, Harm Derksen, Jonathan Gryak et al. Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2018. Cites: paper

Atrial Fibrillation Detection in Short Single Lead ECG Recordings Using Wavelet Transform and Artificial Neural Networks
Fabio Castrillón, Dilio Mendez, Lusvin Javier Amado Forero et al. Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2018. Cites: paper

AutoModeling: Integrated Approach for Automated Model Generation by Ensemble Selection of Feature Subset and Classifier
Arijit Ukil, Ishan Sahu, Chetanya Puri et al. International Joint Conference on Neural Networks (IJCNN), 2018. Cites: paper

Detection of Atrial Fibrillation from RR Intervals and PQRST Morphology using a Neural Network Ensemble
Heba Khamis, Jiayu Chen, J. Stephen Redmond et al. Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2018. Cites: paper

Integrated IoT intelligent system for the automatic detection of cardiac variability
Antonio Martínez-Millana, Carmen Palao, Carlos Fernández-Llatas et al. Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2018. Cites: paper

On the adoption of abductive reasoning for time series interpretation
Tomás Teijeiro, Paulo Félix. Artificial Intelligence, 2018. Cites: paper

Detecting and interpreting myocardial infarctions using fully convolutional neural networks.
Nils Strodthoff, Claas Strodthoff. arXiv (Cornell University), 2018. Cites: paper

A comparison of entropy approaches for AF discrimination
Chengyu Liu, Julien Oster, Erik Reinertsen et al. Physiological Measurement, 2018. Cites: paper

SQI Quality Evaluation Mechanism of Single-Lead ECG Signal Based on Simple Heuristic Fusion and Fuzzy Comprehensive Evaluation
Zhidong Zhao, Yefei Zhang. Frontiers in Physiology, 2018. Cites: paper

ECGNet: Deep Network for Arrhythmia Classification
Balamurali Murugesan, Vignesh Ravichandran, Keerthi Ram et al. IEEE International Symposium on Medical Measurements and Applications (MeMeA), 2018. Cites: paper

A support vector machine approach for AF classification from a short single-lead ECG recording
Na Liu, Muyi Sun, Ludi Wang et al. Physiological Measurement, 2018. Cites: paper

A low-complexity algorithm for detection of atrial fibrillation using an ECG
Nadi Sadr, Madhuka Jayawardhana, Thuy Thi Thanh Pham et al. Physiological Measurement, 2018. Cites: paper

Detecting atrial fibrillation from short single lead ECGs using statistical and morphological features
Mohamed Athif, Pamodh Chanuka Yasawardene, Chathuri Daluwatte. Physiological Measurement, 2018. Cites: paper

Learning representations for multivariate time series with missing data using Temporal Kernelized Autoencoders
Filippo Maria Bianchi, Lorenzo Livi, Karl Øyvind Mikalsen et al. arXiv (Cornell University), 2018. Cites: paper

Cardiac Arrhythmia Classification by Multi-Layer Perceptron and Convolution Neural Networks
Shalin Savalia, Vahid Emamian. Bioengineering, 2018. Cites: paper

Atrial fibrillation classification using step-by-step machine learning
Sebastian D. Goodfellow, Andrew Goodwin, Robert Greer et al. Biomedical Physics & Engineering Express, 2018. Cites: paper

A hybrid feature extraction method to detect Atrial Fibrillation from single lead ECG recording
Ruhi Mahajan, Rishikesan Kamaleswaran, Oğuz Akbilgiç. IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI ...), 2018. Cites: paper

Visualisation of long-term ECG signals applied to post-intensive care patients
Delaram Jarchi, Adam Mahdi, Lionel Tarassenko et al. Wearable and Implantable Body Sensor Networks, 2018. Cites: paper

Model-Based Assessment of f-Wave Signal Quality in Patients With Atrial Fibrillation
Mikael Henriksson, Andrius Petrėnas, Vaidotas Marozas et al. IEEE Transactions on Biomedical Engineering, 2018. Cites: paper

Not to Cry Wolf: Distantly Supervised Multitask Learning in Critical Care
Patrick Schwab, E. Keller, Carl Muroi et al. arXiv (Cornell University), 2018. Cites: paper

Databases and Simulation
Leif Sörnmo, Andrius Petrėnas, Vaidotas Marozas. Series in bioengineering, 2018. Cites: paper

Detection of Atrial Fibrillation
Leif Sörnmo, Andrius Petrėnas, Vaidotas Marozas. Series in bioengineering, 2018. Cites: paper

Evaluation of the Signal Quality of Wrist-Based Photoplethysmography
Nikhilesh Pradhan. 2018. Cites: paper

Multiclass classification of myocardial infarction with convolutional and recurrent neural networks for portable ECG devices
Hin Wai Lui, King Lau Chow. Informatics in Medicine Unlocked, 2018. Cites: paper

Heart rate compression & time reduction method for HRV monitoring in athletes
Sajad Darabi, Babak Moatamed, Wenhao Huang et al. IEEE Healthcare Innovations and Point of Care Technologies Conference (HI-POCT), 2017. Cites: paper

Deep Learning for ECG Classification
Boris Pyakillya, Н. Я. Казаченко, N Mikhailovsky. Journal of Physics Conference Series, 2017. Cites: paper

AF Classification from ECG Recording Using Feature Ensemble and Sparse Coding
Bradley M. Whitaker, Muhammed Rizwan, Varol Burak Aydemir et al. Computing in cardiology, 2017. Cites: paper

AF Detection and ECG Classification�based on Convolutional Recurrent Neural Network
Mohamed Limam, Fŕed́eric Precioso. Computing in cardiology, 2017. Cites: paper

A Hierarchical Cardiac Rhythm Classification Methodology Based on Electrocardiogram Fiducial Points
Dionisije Sopic, Elisabetta De Giovanni, Amir Aminifar et al. Computing in cardiology, 2017. Cites: paper

Arrhythmia Classification from the Abductive Interpretation of Short Single-Lead ECG Records
Tomás Teijeiro, Constantino Antonio García Martínez, Daniel Castro et al. Computing in cardiology, 2017. Cites: paper

Atrial Fibrillation Classification from a Short Single Lead ECG Recording Using Hierarchical Classifier
Erin E. Coppola, Prashnna Gyawali, Nihar Vanjara et al. Computing in cardiology, 2017. Cites: paper

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