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Machine learning (ML) has recently shown promising results in medical predictions using electronic health records (EHRs).
A new measure of rank correlation
Maurice G Kendall · 1938
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On a test of whether one of two random variables is stochastically larger than the other
Henry B Mann and Donald R Whitney · 1947
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Learning internal representations by error propagation
David E Rumelhart, Geoffrey E Hinton, and Ronald J Williams · 1985
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Serial evaluation of the sofa score to predict outcome in critically ill patients
Flavio Lopes Ferreira, Daliana Peres Bota, Annette Bross, Christian Mélot, and Jean-Louis Vincent · 2001
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Overview of the trec 2014 clinical decision support track
Matthew S Simpson, Ellen M Voorhees, and William R Hersh · 2014
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Overview of the trec 2015 clinical decision support track
Kirk Roberts, Matthew S. Simpson, Ellen M. Voorhees, and William R. Hersh · 2015
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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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Mimic-iii, a freely accessible critical care database
Alistair EW Johnson, Tom J Pollard, Lu Shen, Li-wei H Lehman, Mengling Feng, Mohammad Ghassemi, Benjamin Moody, Peter Szolovits, Leo Anthony Celi, and Roger G Mark · 2016
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Overview of the trec 2016 clinical decision support track
Kirk Roberts, Dina Demner-Fushman, Ellen M. Voorhees, and William R. Hersh · 2016
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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The eicu collaborative research database, a freely available multi-center database for critical care research
Tom J Pollard, Alistair EW Johnson, Jesse D Raffa, Leo A Celi, Roger G Mark, and Omar Badawi · 2018
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Scalable and accurate deep learning with electronic health records
Alvin Rajkomar, Eyal Oren, Kai Chen, Andrew M Dai, Nissan Hajaj, Michaela Hardt, Peter J Liu, Xiaobing Liu, Jake Marcus, Mimi Sun, et al · 2018
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Big data and data science in critical care
L Nelson Sanchez-Pinto, Yuan Luo, and Matthew M Churpek · 2018
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Embedding electronic health records for clinical information retrieval
Xing Wei and Carsten Eickhoff · 2018
Cited alongside, same era.
Publicly available clinical bert embeddings
Emily Alsentzer, John R Murphy, Willie Boag, Wei-Hung Weng, Di Jin, Tristan Naumann, WA Redmond, and Matthew BA McDermott · 2019
Cited alongside, same era.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
Cited alongside, same era.
Rethinking attention with performers
Krzysztof Marcin Choromanski, Valerii Likhosherstov, David Dohan, Xingyou Song, Andreea Gane, Tamas Sarlos, Peter Hawkins, Jared Quincy Davis, Afroz Mohiuddin, Lukasz Kaiser, et al · 2020
Cited alongside, same era.
Dynamic survival prediction in intensive care units from heterogeneous time series without the need for variable selection or curation
Jacob Deasy, Pietro Liò, and Ari Ercole · 2020
Cited alongside, same era.
A comprehensive ehr timeseries pre-training benchmark
Matthew McDermott, Bret Nestor, Evan Kim, Wancong Zhang, Anna Goldenberg, Peter Szolovits, and Marzyeh Ghassemi · 2021
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Language models are an effective representation learning technique for electronic health record data
Ethan Steinberg, Ken Jung, Jason A Fries, Conor K Corbin, Stephen R Pfohl, and Nigam H Shah · 2021
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Sharing icu patient data responsibly under the society of critical care medicine/european society of intensive care medicine joint data science collaboration: the amsterdam university medical centers database (amsterdamumcdb) example
Patrick J Thoral, Jan M Peppink, Ronald H Driessen, Eric JG Sijbrands, Erwin JO Kompanje, Lewis Kaplan, Heatherlee Bailey, Jozef Kesecioglu, Maurizio Cecconi, Matthew Churpek, et al · 2021
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Finetuned language models are zero-shot learners
Jason Wei, Maarten Bosma, Vincent Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M Dai, and Quoc V Le · 2021
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Medretriever: Target-driven interpretable health risk prediction via retrieving unstructured medical text
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Early prediction of circulatory failure in the intensive care unit using machine learning
Stephanie L Hyland, Martin Faltys, Matthias Hüser, Xinrui Lyu, Thomas Gumbsch, Cristóbal Esteban, Christian Bock, Max Horn, Michael Moor, Bastian Rieck, et al · 2020
Cited alongside, same era.
Mimic-iv
Alistair Johnson, Lucas Bulgarelli, Tom Pollard, Steven Horng, Leo Anthony Celi, and Roger Mark · 2020
Cited alongside, same era.
Dense passage retrieval for open-domain question answering
Vladimir Karpukhin, Barlas Oguz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih · 2020
Cited alongside, same era.
Retrieval-augmented generation for knowledge-intensive nlp tasks
Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, et al · 2020
Cited alongside, same era.
Anubhav Reddy Nallabasannagari, Madhu Reddiboina, Ryan Seltzer, Trevor Zeffiro, Ajay Sharma, and Mahendra Bhandari · 2020
Cited alongside, same era.
Long range arena: A benchmark for efficient transformers
Yi Tay, Mostafa Dehghani, Samira Abnar, Yikang Shen, Dara Bahri, Philip Pham, Jinfeng Rao, Liu Yang, Sebastian Ruder, and Donald Metzler · 2020
Cited alongside, same era.
Mimic-extract: A data extraction, preprocessing, and representation pipeline for mimic-iii
Shirly Wang, Matthew BA McDermott, Geeticka Chauhan, Marzyeh Ghassemi, Michael C Hughes, and Tristan Naumann · 2020
Cited alongside, same era.
Muchao Ye, Suhan Cui, Yaqing Wang, Junyu Luo, Cao Xiao, and Fenglong Ma · 2021
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Improving language models by retrieving from trillions of tokens
Sebastian Borgeaud, Arthur Mensch, Jordan Hoffmann, Trevor Cai, Eliza Rutherford, Katie Millican, George Bm Van Den Driessche, Jean-Baptiste Lespiau, Bogdan Damoc, Aidan Clark, et al · 2022
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Recurrent memory transformer
Aydar Bulatov, Yury Kuratov, and Mikhail Burtsev · 2022
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Unifying heterogeneous electronic health records systems via text-based code embedding
Kyunghoon Hur, Jiyoung Lee, Jungwoo Oh, Wesley Price, Younghak Kim, and Edward Choi · 2022
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Mega: Moving average equipped gated attention
Xuezhe Ma, Chunting Zhou, Xiang Kong, Junxian He, Liangke Gui, Graham Neubig, Jonathan May, and Luke Zettlemoyer · 2022
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Literature-augmented clinical outcome prediction
Aakanksha Naik, Sravanthi Parasa, Sergey Feldman, Lucy Lu Wang, and Tom Hope · 2022
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Scaling transformer to 1m tokens and beyond with rmt
Aydar Bulatov, Yuri Kuratov, and Mikhail S Burtsev · 2023
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Genhpf: General healthcare predictive framework for multi-task multi-source learning
Kyunghoon Hur, Jungwoo Oh, Junu Kim, Jiyoun Kim, Min Jae Lee, Eunbyeol Cho, Seong-Eun Moon, Young-Hak Kim, Louis Atallah, and Edward Choi · 2023
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Conceptualizing machine learning for dynamic information retrieval of electronic health record notes
Sharon Jiang, Shannon Shen, Monica Agrawal, Barbara Lam, Nicholas Kurtzman, Steven Horng, David R Karger, and David Sontag · 2023
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