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Modern healthcare is ripe for disruption by AI.
Finding structure in time
Jeffrey L Elman · 1990
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Limitations of applying summary results of clinical trials to individual patients: the need for risk stratification
David M Kent and Rodney A Hayward · 2007
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Natural language processing (almost) from scratch
Ronan Collobert, Jason Weston, Léon Bottou, Michael Karlen, Koray Kavukcuoglu, and Pavel Kuksa · 2011
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From machine learning to machine reasoning
Léon Bottou · 2014
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Adam: A method for stochastic optimization
Diederik Kingma and Jimmy Ba · 2014
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Regularizing RNNs by Stabilizing Activations
David Krueger and Roland Memisevic · 2015
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Deep learning
Yann LeCun, Yoshua Bengio, and Geoffrey Hinton · 2015
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Learning vector representation of medical objects via EMR-driven nonnegative restricted Boltzmann machines (eNRBM)
Truyen Tran, Tu Dinh Nguyen, Dinh Phung, and Svetha Venkatesh · 2015
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Risk prediction with electronic health records: A deep learning approach
Yu Cheng, Fei Wang, Ping Zhang, and Jianying Hu · 2016
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Multi-layer representation learning for medical concepts
Edward Choi, Mohammad Taha Bahadori, Elizabeth Searles, Catherine Coffey, and Jimeng Sun · 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
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Guest editorial deep learning in medical imaging: Overview and future promise of an exciting new technique
Hayit Greenspan, Bram van Ginneken, and Ronald M Summers · 2016
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Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs
Varun Gulshan, Lily Peng, Marc Coram, Martin C Stumpe, Derek Wu, Arunachalam Narayanaswamy, Subhashini Venugopalan, Kasumi Widner, Tom Madams, Jorge Cuadros, et al · 2016
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Deepr: A Convolutional Net for Medical Records
Phuoc Nguyen, Truyen Tran, Nilmini Wickramasinghe, and Svetha Venkatesh · 2017
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Predicting healthcare trajectories from medical records: A deep learning approach
Trang Pham, Truyen Tran, Dinh Phung, and Svetha Venkatesh · 2017
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One size fits many: Column bundle for multi-x learning
Trang Pham, Truyen Tran, and Svetha Venkatesh · 2017
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Deep learning for health informatics
Daniele Ravì, Charence Wong, Fani Deligianni, Melissa Berthelot, Javier Andreu-Perez, Benny Lo, and Guang-Zhong Yang · 2017
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Deep EHR: A Survey of Recent Advances in Deep Learning Techniques for Electronic Health Record (EHR) Analysis
Benjamin Shickel, Patrick James Tighe, Azra Bihorac, and Parisa Rashidi · 2017
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Order matters: Sequence to sequence for sets
Oriol Vinyals, Samy Bengio, and Manjunath Kudlur · 2016
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Knet: beginning deep learning with 100 lines of julia
Deniz Yuret · 2016
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Dermatologist-level classification of skin cancer with deep neural networks
Andre Esteva, Brett Kuprel, Roberto A Novoa, Justin Ko, Susan M Swetter, Helen M Blau, and Sebastian Thrun · 2017
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Deepsetnet: Predicting sets with deep neural networks
S Hamid Rezatofighi, BG Kumar, Anton Milan, Ehsan Abbasnejad, Anthony Dick, Ian Reid, et al · 2017
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Deep learning for biomedicine: A tutorial
Truyen Tran · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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Deep sets
Manzil Zaheer, Satwik Kottur, Siamak Ravanbakhsh, Barnabas Poczos, Ruslan Salakhutdinov, and Alexander Smola · 2017
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