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Transformers have significantly advanced the modeling of Electronic Health Records (EHR), yet their deployment in real-world healthcare is limited by several key challenges.
Early detection of heart failure using electronic health records: Practical implications for time before diagnosis, data diversity, data quantity, and data density
Kenney Ng, Steven R. Steinhubl, Christopher deFilippi, Sanjoy Dey, and Walter F. Stewart · 1941
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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PhysioBank, PhysioToolkit, and PhysioNet: Components of a new research resource for complex physiologic signals
A. L. Goldberger, L. A. N. Amaral, L. Glass, J. M. Hausdorff, P. Ch. Ivanov, R. G. Mark, J. E. Mietus, G. B. Moody, C.-K. Peng, and H. E. Stanley · 2000
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Risk-adjusting hospital inpatient mortality using automated inpatient, outpatient, and laboratory databases
Gabriel J. Escobar, John D. Greene, Peter Scheirer, Marla N. Gardner, David Draper, and Patricia Kipnis · 2008
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Modifying icd-9-cm coding of secondary diagnoses to improve risk-adjustment of inpatient mortality rates
Michael Pine, Harmon S. Jordan, Anne Elixhauser, Donald E. Fry, David C. Hoaglin, Barbara Jones, Roger Meimban, David Warner, and Junius Gonzales · 2009
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Length of stay predictions: Improvements through the use of automated laboratory and comorbidity variables
Vincent Liu, Patricia Kipnis, Michael K. Gould, and Gabriel J. Escobar · 2010
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A public-private partnership develops and externally validates a 30-day hospital readmission risk prediction model
Shahid Ali Choudhry, Jing Li, Darcy Davis, Cole Erdmann, Rishi Sikka, and Bharat Sutariya · 2013
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Efficient estimation of word representations in vector space, 2013
Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean · 2013
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Development and validation of a continuous measure of patient condition using the electronic medical record
Michael J. Rothman, Steven I. Rothman, and Joseph Beals · 2013
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Using electronic health record data to develop inpatient mortality predictive model: Acute laboratory risk of mortality score (alarms)
Ying P Tabak, Xiaowu Sun, Carlos M Nunez, and Richard S Johannes · 2013
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Dropout: A simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov · 2014
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The effects of data sources, cohort selection, and outcome definition on a predictive model of risk of thirty-day hospital readmissions
Colin Walsh and George Hripcsak · 2014
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Semantic processing of ehr data for clinical research
Hong Sun, Kristof Depraetere, Jos De Roo, Giovanni Mels, Boris De Vloed, Marc Twagirumukiza, and Dirk Colaert · 2015
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Layer normalization, 2016
Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E. Hinton · 2016
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Xgboost: A scalable tree boosting system
Tianqi Chen and Carlos Guestrin · 2016
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Learning low-dimensional representations of medical concepts
Youngduck Choi, Chill Yi-I. Chiu, and David Sontag · 2016
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Real-time automated sampling of electronic medical records predicts hospital mortality
Hargobind S. Khurana, Robert H. Groves, Michael P. Simons, Mary Martin, Brenda Stoffer, Sherri Kou, Richard Gerkin, Eric Reiman, and Sairam Parthasarathy · 2016
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Smart on fhir: a standards-based, interoperable apps platform for electronic health records
Joshua C Mandel, David A Kreda, Kenneth D Mandl, Isaac S Kohane, and Rachel B Ramoni · 2016
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Predicting all-cause readmissions using electronic health record data from the entire hospitalization: Model development and comparison
Oanh Kieu Nguyen, Anil N. Makam, Christopher Clark, Song Zhang, Bin Xie, Ferdinand Velasco, Ruben Amarasingham, and Ethan A. Halm · 2016
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Multi-task prediction of disease onsets from longitudinal lab tests, 2016
Narges Razavian, Jake Marcus, and David Sontag · 2016
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Sigmoid-weighted linear units for neural network function approximation in reinforcement learning, 2017
Stefan Elfwing, Eiji Uchibe, and Kenji Doya · 2017
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Adam: A method for stochastic optimization, 2017
Diederik P. Kingma and Jimmy Ba · 2017
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Axiomatic attribution for deep networks, 2017
Mukund Sundararajan, Ankur Taly, and Qiqi Yan · 2017
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Scalable and accurate deep learning for electronic health records
Alvin Rishi Rajkomar, Eyal Oren, Kai Chen, Andrew Dai, Nissan Hajaj, Mila Hardt, Peter J. Liu, Xiaobing Liu, Jake Marcus, Mimi Sun, Patrik Per Sundberg, Hector Yee, Kun Zhang, Yi Zhang, Gerardo Flores, Gavin Duggan, Jamie Irvine, Quoc Le, Kurt Litsch, Alex Mossin, Justin Jesada Tansuwan, De Wang, James Wexler, Jimbo Wilson, Dana Ludwig, Samuel Volchenboum, Kat Chou, Michael Pearson, Srinivasan Madabushi, Nigam Shah, Atul Butte, Michael Howell, Claire Cui, Greg Corrado, and Jeff Dean · 2018
Cited alongside, same era.
The potential for artificial intelligence in healthcare
Thomas Davenport and Ravi Kalakota · 2019
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Bert: Pre-training of deep bidirectional transformers for language understanding, 2019
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
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Mamba: Linear-time sequence modeling with selective state spaces, 2023
Albert Gu and Tri Dao · 2023
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Duett: Dual event time transformer for electronic health records, 2023
Alex Labach, Aslesha Pokhrel, Xiao Shi Huang, Saba Zuberi, Seung Eun Yi, Maksims Volkovs, Tomi Poutanen, and Rahul G. Krishnan · 2023
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Crosslingual generalization through multitask finetuning, 2023
Niklas Muennighoff, Thomas Wang, Lintang Sutawika, Adam Roberts, Stella Biderman, Teven Le Scao, M Saiful Bari, Sheng Shen, Zheng-Xin Yong, Hailey Schoelkopf, Xiangru Tang, Dragomir Radev, Alham Fikri Aji, Khalid Almubarak, Samuel Albanie, Zaid Alyafeai, Albert Webson, Edward Raff, and Colin Raffel · 2023
Later among the works it cites.
ExBEHRT: Extended Transformer for Electronic Health Records , page 73–84
Maurice Rupp, Oriane Peter, and Thirupathi Pattipaka · 2023
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Attention is all you need, 2023
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin · 2023
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Time2vec: Learning a vector representation of time, 2019
Seyed Mehran Kazemi, Rishab Goel, Sepehr Eghbali, Janahan Ramanan, Jaspreet Sahota, Sanjay Thakur, Stella Wu, Cathal Smyth, Pascal Poupart, and Marcus Brubaker · 2019
Cited alongside, same era.
Decoupled weight decay regularization, 2019
Ilya Loshchilov and Frank Hutter · 2019
Cited alongside, same era.
Time-sensitive clinical concept embeddings learned from large electronic health records
Yang Xiang, Jun Xu, Yuqi Si, Zhiheng Li, Laila Rasmy, Yujia Zhou, Firat Tiryaki, Fang Li, Yaoyun Zhang, Yonghui Wu, Xiaoqian Jiang, Wenjin Jim Zheng, Degui Zhi, Cui Tao, and Hua Xu · 2019
Cited alongside, same era.
Root mean square layer normalization, 2019
Biao Zhang and Rico Sennrich · 2019
Cited alongside, same era.
Clinical concept embeddings learned from massive sources of multimodal medical data
Andrew L. Beam, Benjamin Kompa, Allen Schmaltz, Inbar Fried, Griffin Weber, Nathan Palmer, Xu Shi, Tianxi Cai, and Isaac S. Kohane · 2020
Cited alongside, same era.
Language models are an effective patient representation learning technique for electronic health record data, 2020
Ethan Steinberg, Ken Jung, Jason A. Fries, Conor K. Corbin, Stephen R. Pfohl, and Nigam H. Shah · 2020
Cited alongside, same era.
Huggingface’s transformers: State-of-the-art natural language processing, 2020
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander M. Rush · 2020
Cited alongside, same era.
Multitask prompt tuning enables parameter-efficient transfer learning, 2023
Zhen Wang, Rameswar Panda, Leonid Karlinsky, Rogerio Feris, Huan Sun, and Yoon Kim · 2023
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The shaky foundations of large language models and foundation models for electronic health records
Michael Wornow, Yizhe Xu, Rahul Thapa, Birju Patel, Ethan Steinberg, Scott Fleming, Michael A. Pfeffer, Jason Fries, and Nigam H. Shah · 2023
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An iterative self-learning framework for medical domain generalization
Zhenbang Wu, Huaxiu Yao, David Liebovitz, and Jimeng Sun · 2023
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Vision transformers need registers, 2024
Timothée Darcet, Maxime Oquab, Julien Mairal, and Piotr Bojanowski · 2024
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Codontransformer: a multispecies codon optimizer using context-aware neural networks
Adibvafa Fallahpour, Vincent Gureghian, Guillaume J. Filion, Ariel B. Lindner, and Amir Pandi · 2024
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Foresight—a generative pretrained transformer for modelling of patient timelines using electronic health records: a retrospective modelling study
Zeljko Kraljevic, Dan Bean, Anthony Shek, Rebecca Bendayan, Harry Hemingway, Joshua Au Yeung, Alexander Deng, Alfred Baston, Jack Ross, Esther Idowu, James T Teo, and Richard J B Dobson · 2024
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U-mamba: Enhancing long-range dependency for biomedical image segmentation, 2024
Jun Ma, Feifei Li, and Bo Wang · 2024
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Caduceus: Bi-directional equivariant long-range dna sequence modeling, 2024
Yair Schiff, Chia-Hsiang Kao, Aaron Gokaslan, Tri Dao, Albert Gu, and Volodymyr Kuleshov · 2024
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Is mamba effective for time series forecasting?, 2024
Zihan Wang, Fanheng Kong, Shi Feng, Ming Wang, Xiaocui Yang, Han Zhao, Daling Wang, and Yifei Zhang · 2024
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Integrating mamba and transformer for long-short range time series forecasting, 2024
Xiongxiao Xu, Yueqing Liang, Baixiang Huang, Zhiling Lan, and Kai Shu · 2024
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Transformehr: transformer-based encoder-decoder generative model to enhance prediction of disease outcomes using electronic health records
Zhichao Yang, Avijit Mitra, Weisong Liu, Dan Berlowitz, and Hong Yu · 2041
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Transformers for cardiac patient mortality risk prediction from heterogeneous electronic health records
Emmi Antikainen, Joonas Linnosmaa, Adil Umer, Niku Oksala, Markku Eskola, Mark van Gils, Jussi Hernesniemi, and Moncef Gabbouj · 2045
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Behrt: Transformer for electronic health records
Yikuan Li, Shishir Rao, José Roberto Ayala Solares, Abdelaali Hassaine, Rema Ramakrishnan, Dexter Canoy, Yajie Zhu, Kazem Rahimi, and Gholamreza Salimi-Khorshidi · 2045
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Mimic-iv, a freely accessible electronic health record dataset
Alistair E. W. Johnson, Lucas Bulgarelli, Lu Shen, Alvin Gayles, Ayad Shammout, Steven Horng, Tom J. Pollard, Sicheng Hao, Benjamin Moody, Brian Gow, Li-wei H. Lehman, Leo A. Celi, and Roger G. Mark · 2052
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An electronic health record system implementation in a resource limited country—lessons learned
Sayed K Ali, Haroon Khan, Jasmit Shah, and K Nadeem Ahmed · 2076
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