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Despite the explosion of interest in healthcare AI research, the reproducibility and benchmarking of those research works are often limited due to the lack of standard benchmark datasets and diverse evaluation metrics.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
Earlier work this paper cites.
Face recognition: a convolutional neural-network approach
S. Lawrence, C. L. Giles, Ah Chung Tsoi, and A. D. Back · 1997
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Random forests
Leo Breiman · 2001
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Learning phrase representations using rnn encoder-decoder for statistical machine translation
Kyunghyun Cho, Bart Van Merriënboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio · 2014
Earlier work this paper cites.
Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
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Xgboost: A scalable tree boosting system
Tianqi Chen and Carlos Guestrin · 2016
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Retain: An interpretable predictive model for healthcare using reverse time attention mechanism
Edward Choi, Mohammad Taha Bahadori, Jimeng Sun, Joshua Kulas, Andy Schuetz, and Walter Stewart · 2016
Earlier work this paper cites.
Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
Earlier work this paper cites.
Rethinking the inception architecture for computer vision
Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jon Shlens, and ZB Wojna · 2016
Earlier work this paper cites.
Aggregated residual transformations for deep neural networks
Saining Xie, Ross B. Girshick, Piotr Dollár, Zhuowen Tu, and Kaiming He · 2016
Earlier work this paper cites.
Patient subtyping via time-aware lstm networks
Inci M Baytas, Cao Xiao, Xi Zhang, Fei Wang, Anil K Jain, and Jiayu Zhou · 2017
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Mobilenets: Efficient convolutional neural networks for mobile vision applications
Andrew Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, and Hartwig Adam · 2017
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Densely connected convolutional networks
G. Huang, Z. Liu, L. Van Der Maaten, and K. Q. Weinberger · 2017
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Dipole: Diagnosis prediction in healthcare via attention-based bidirectional recurrent neural networks
Fenglong Ma, Radha Chitta, Jing Zhou, Quanzeng You, Tong Sun, and Jing Gao · 2017
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healthcareai-py v1.0, August 2017
Taylor Miller, Michael Mastanduno, Levi Thatcher, and Taylor Larsen · 2017
Cited alongside, same era.
Explainable prediction of medical codes from clinical text
Multitask learning and benchmarking with clinical time series data
Hrayr Harutyunyan, Hrant Khachatrian, David C Kale, Greg Ver Steeg, and Aram Galstyan · 2019
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MINA: multilevel knowledge-guided attention for modeling electrocardiography signals
Shenda Hong, Cao Xiao, Tengfei Ma, Hongyan Li, and Jimeng Sun · 2019
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Heartbeat classification using deep residual convolutional neural network from 2-lead electrocardiogram
Zhi Li, Dengshi Zhou, Li Wan, Jian Li, and Wenfeng Mou · 2019
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Automatic classification of cad ecg signals with sdae and bidirectional long short-term network
E. K. Wang, X. Zhang, and L. Pan · 2019
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K-margin-based residual-convolution-recurrent neural network for atrial fibrillation detection
Yuxi Zhou, Shenda Hong, Junyuan Shang, Meng Wu, Qingyun Wang, Hongyan Li, and Junqing Xie · 2019
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James Mullenbach, Sarah Wiegreffe, Jon Duke, Jimeng Sun, and Jacob Eisenstein · 2018
Cited alongside, same era.
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, Bryan Conroy, and Saeed Babaeizadeh · 2018
Cited alongside, same era.
Opportunities and challenges in developing deep learning models using electronic health records data: a systematic review
Cao Xiao, Edward Choi, and Jimeng Sun · 2018
Cited alongside, same era.
Raim: Recurrent attentive and intensive model of multimodal patient monitoring data
Yanbo Xu, Siddharth Biswal, Shriprasad R Deshpande, Kevin O Maher, and Jimeng Sun · 2018
Cited alongside, same era.
A novel wavelet sequence based on deep bidirectional lstm network model for ecg signal classification
Özal Yildirim · 2018
Cited alongside, same era.
Dr. Agent: Clinical predictive model via mimicked second opinions
Junyi Gao, Cao Xiao, Lucas M Glass, and Jimeng Sun
Cited in the paper.
Stagenet: Stage-aware neural networks for health risk prediction
Junyi Gao, Cao Xiao, Yasha Wang, Wen Tang, Lucas M Glass, and Jimeng Sun · 2020
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Dilated convolutional attention network for medical code assignment from clinical text
Shaoxiong Ji, Erik Cambria, and Pekka Marttinen · 2020
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Icd coding from clinical text using multi-filter residual convolutional neural network
Fei Li and Hong Yu · 2020
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FLANNEL: Focal Loss Based Neural Network Ensemble for COVID-19 Detection
Zhi Qiao, Austin Bae, Lucas M Glass, Cao Xiao, and Jimeng Sun · 2020
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A label attention model for icd coding from clinical text
Thanh Vu, Dat Quoc Nguyen, and Anthony Nguyen · 2020
Later among the works it cites.