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references.bib
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@inproceedings{Pham2016,
title={Deepcare: A deep dynamic memory model for predictive medicine},
author={Pham, Trang and Tran, Truyen and Phung, Dinh and Venkatesh, Svetha},
booktitle={Pacific-Asia Conference on Knowledge Discovery and Data Mining},
pages={30--41},
year={2016},
organization={Springer}
}
@article{Lin2013,
title={Network in network},
author={Lin, Min and Chen, Qiang and Yan, Shuicheng},
journal={arXiv preprint arXiv:1312.4400},
year={2013}
}
@article{He2015,
author = {Kaiming He and
Xiangyu Zhang and
Shaoqing Ren and
Jian Sun},
title = {Deep Residual Learning for Image Recognition},
journal = {CoRR},
volume = {abs/1512.03385},
year = {2015},
url = {http://arxiv.org/abs/1512.03385},
archivePrefix = {arXiv},
eprint = {1512.03385},
timestamp = {Wed, 07 Jun 2017 14:41:17 +0200},
biburl = {http://dblp.org/rec/bib/journals/corr/HeZRS15},
bibsource = {dblp computer science bibliography, http://dblp.org}
}
@article{Simonyan2015,
title={Very deep convolutional networks for large-scale image recognition},
author={Simonyan, Karen and Zisserman, Andrew},
journal={arXiv preprint arXiv:1409.1556},
year={2014}
}
@inproceedings{Krizhevsky2012,
title={Imagenet classification with deep convolutional neural networks},
author={Krizhevsky, Alex and Sutskever, Ilya and Hinton, Geoffrey E},
booktitle={Advances in neural information processing systems},
pages={1097--1105},
year={2012}
}
@article{Dwork2015,
title={The reusable holdout: Preserving validity in adaptive data analysis},
author={Dwork, Cynthia and Feldman, Vitaly and Hardt, Moritz and Pitassi, Toniann and Reingold, Omer and Roth, Aaron},
journal={Science},
volume={349},
number={6248},
pages={636--638},
year={2015},
publisher={American Association for the Advancement of Science}
}
@article{Lipton2016a,
title={Learning to diagnose with LSTM recurrent neural networks},
author={Lipton, Zachary C and Kale, David C and Elkan, Charles and Wetzell, Randall},
journal={arXiv preprint arXiv:1511.03677},
year={2015}
}
@article{Rothman2013,
title={Development and validation of a continuous measure of patient condition using the electronic medical record},
author={Rothman, Michael J and Rothman, Steven I and Beals, Joseph},
journal={Journal of biomedical informatics},
volume={46},
number={5},
pages={837--848},
year={2013},
publisher={Elsevier}
}
@article{Che2016,
title={Recurrent neural networks for multivariate time series with missing values},
author={Che, Zhengping and Purushotham, Sanjay and Cho, Kyunghyun and Sontag, David and Liu, Yan},
journal={arXiv preprint arXiv:1606.01865},
year={2016}
}
@inproceedings{Choi2016,
title={Doctor ai: Predicting clinical events via recurrent neural networks},
author={Choi, Edward and Bahadori, Mohammad Taha and Schuetz, Andy and Stewart, Walter F and Sun, Jimeng},
booktitle={Machine Learning for Healthcare Conference},
pages={301--318},
year={2016}
}
@article{Miotto2016,
title={Deep patient: An unsupervised representation to predict the future of patients from the electronic health records},
author={Miotto, Riccardo and Li, Li and Kidd, Brian A and Dudley, Joel T},
journal={Scientific reports},
volume={6},
pages={26094},
year={2016},
publisher={Nature Publishing Group}
}
@article{Nguyen2016,
title={Deepr: A Convolutional Net for Medical Records},
author={Nguyen, Phuoc and Tran, Truyen and Wickramasinghe, Nilmini and Venkatesh, Svetha},
journal={arXiv preprint arXiv:1607.07519},
year={2016}
}
@inproceedings{Lipton2016,
title={Directly modeling missing data in sequences with RNNs: Improved classification of clinical time series},
author={Lipton, Zachary C and Kale, David and Wetzel, Randall},
booktitle={Machine Learning for Healthcare Conference},
pages={253--270},
year={2016}
}
@article{Suresh2017,
title={Clinical Intervention Prediction and Understanding using Deep Networks},
author={Suresh, Harini and Hunt, Nathan and Johnson, Alistair and Celi, Leo Anthony and Szolovits, Peter and Ghassemi, Marzyeh},
journal={arXiv preprint arXiv:1705.08498},
year={2017}
}