Jonathan Rubin
Jonathan Rubin
Research Scientist, Amazon Alexa AI
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Zitiert von
Zitiert von
Classifying heart sound recordings using deep convolutional neural networks and mel-frequency cepstral coefficients
J Rubin, R Abreu, A Ganguli, S Nelaturi, I Matei, K Sricharan
2016 Computing in cardiology conference (CinC), 813-816, 2016
Computer poker: A review
J Rubin, I Watson
Artificial intelligence 175 (5-6), 958-987, 2011
Recognizing abnormal heart sounds using deep learning
J Rubin, R Abreu, A Ganguli, S Nelaturi, I Matei, K Sricharan
arXiv preprint arXiv:1707.04642, 2017
A wide and deep transformer neural network for 12-lead ECG classification
A Natarajan, Y Chang, S Mariani, A Rahman, G Boverman, S Vij, J Rubin
2020 Computing in Cardiology, 1-4, 2020
Cardiac arrhythmia detection using deep learning: A review
S Parvaneh, J Rubin, S Babaeizadeh, M Xu-Wilson
Journal of electrocardiology 57, S70-S74, 2019
Large scale automated reading of frontal and lateral chest x-rays using dual convolutional neural networks
J Rubin, D Sanghavi, C Zhao, K Lee, A Qadir, M Xu-Wilson
arXiv preprint arXiv:1804.07839, 2018
Densely connected convolutional networks for detection of atrial fibrillation from short single-lead ECG recordings
J Rubin, S Parvaneh, A Rahman, B Conroy, S Babaeizadeh
Journal of electrocardiology 51 (6), S18-S21, 2018
Ischemic stroke lesion segmentation in CT perfusion scans using pyramid pooling and focal loss
SM Abulnaga, J Rubin
Brainlesion: glioma, multiple sclerosis, stroke and traumatic brain injuries …, 2019
Densely connected convolutional networks and signal quality analysis to detect atrial fibrillation using short single-lead ECG recordings
J Rubin, S Parvaneh, A Rahman, B Conroy, S Babaeizadeh
2017 Computing in cardiology (cinc), 1-4, 2017
An ensemble boosting model for predicting transfer to the pediatric intensive care unit
J Rubin, C Potes, M Xu-Wilson, J Dong, A Rahman, H Nguyen, ...
International journal of medical informatics 112, 15-20, 2018
Analyzing single-lead short ECG recordings using dense convolutional neural networks and feature-based post-processing to detect atrial fibrillation
S Parvaneh, J Rubin, A Rahman, B Conroy, S Babaeizadeh
Physiological measurement 39 (8), 084003, 2018
Towards a mobile and wearable system for predicting panic attacks
J Rubin, H Eldardiry, R Abreu, S Ahern, H Du, A Pattekar, DG Bobrow
Proceedings of the 2015 ACM International Joint Conference on Pervasive and …, 2015
Similarity-based retrieval and solution re-use policies in the game of Texas Hold’em
J Rubin, I Watson
International Conference on Case-Based Reasoning, 465-479, 2010
A wearable and mobile intervention delivery system for individuals with panic disorder
L Cruz, J Rubin, R Abreu, S Ahern, H Eldardiry, DG Bobrow
Proceedings of the 14th International Conference on Mobile and Ubiquitous …, 2015
Method and a system for providing hosted services based on a generalized model of a health/wellness program
A Ram, GM Youngblood, PL Pirolli, LD Nelson, J Vig, SP Ahern, J Rubin, ...
US Patent 9,898,789, 2018
Electrocardiogram monitoring and interpretation: from traditional machine learning to deep learning, and their combination
S Parvaneh, J Rubin
2018 Computing in Cardiology Conference (CinC) 45, 1-4, 2018
Detecting Steiner and linear isometries operads
J Rubin
Glasgow Mathematical Journal 63 (2), 307-342, 2021
CT-To-MR conditional generative adversarial networks for ischemic stroke lesion segmentation
J Rubin, SM Abulnaga
2019 IEEE International conference on healthcare informatics (ICHI), 1-7, 2019
System and method for automatic objective reporting via wearable sensors
J Rubin, GM Youngblood, A Ram, PL Pirolli, J Vig, SP Ahern, LD Nelson
US Patent 9,672,482, 2017
Case-based strategies in computer poker
J Rubin, I Watson
AI communications 25 (1), 19-48, 2012
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