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We present BEEP (Biomedical Evidence-Enhanced Predictions), a novel approach for clinical outcome prediction that retrieves patient-specific medical literature and incorporates it into predictive models.
The umls metathesaurus: representing different views of biomedical concepts
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Evidence based medicine: what it is and what it isn’t
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Principles of biomedical ethics
Tom L Beauchamp, James F Childress, et al. 2001 · 2001
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Evaluation of negation phrases in narrative clinical reports
Wendy W Chapman, Will Bridewell, Paul Hanbury, Gregory F Cooper, and Bruce G Buchanan. 2001 · 2001
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Context: an algorithm for determining negation, experiencer, and temporal status from clinical reports
Henk Harkema, John N Dowling, Tyler Thornblade, and Wendy W Chapman. 2009 · 2009
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Mayo clinical text analysis and knowledge extraction system (ctakes): architecture, component evaluation and applications
Guergana K Savova, James J Masanz, Philip V Ogren, Jiaping Zheng, Sunghwan Sohn, Karin C Kipper-Schuler, and Christopher G Chute. 2010 · 2010
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2010 i2b2/va challenge on concepts, assertions, and relations in clinical text
Özlem Uzuner, Brett R South, Shuying Shen, and Scott L DuVall. 2011 · 2010
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Two-stage learning to rank for information retrieval
Van Dang, Michael Bendersky, and W Bruce Croft. 2013 · 2013
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Alarm fatigue: a patient safety concern
Sue Sendelbach and Marjorie Funk. 2013 · 2013
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Overview of the trec 2014 clinical decision support track
Matthew S Simpson, Ellen M Voorhees, and William Hersh. 2014 · 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 · 2015
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Mimic-iii, a freely accessible critical care database
Alistair EW Johnson, Tom J Pollard, Lu Shen, H Lehman Li-Wei, Mengling Feng, Mohammad Ghassemi, Benjamin Moody, Peter Szolovits, Leo Anthony Celi, and Roger G Mark. 2016 · 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 · 2016
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What’s in a note? unpacking predictive value in clinical note representations
Willie Boag, Dustin Doss, Tristan Naumann, and Peter Szolovits. 2018 · 2018
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Improving hospital mortality prediction with medical named entities and multimodal learning
Mengqi Jin, Mohammad Taha Bahadori, Aaron Colak, Parminder Bhatia, Busra Celikkaya, Ram Bhakta, Selvan Senthivel, Mohammed Khalilia, Daniel Navarro, Borui Zhang, et al. 2018 · 2018
Cited alongside, same era.
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 · 2018
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Publicly available clinical BERT embeddings
Emily Alsentzer, John Murphy, William Boag, Wei-Hung Weng, Di Jindi, Tristan Naumann, and Matthew McDermott. 2019 · 2019
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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An analysis of attention over clinical notes for predictive tasks
Sarthak Jain, Ramin Mohammadi, and Byron C Wallace. 2019 · 2019
Cited alongside, same era.
Towards unstructured mortality prediction with free-text clinical notes
Mohammad Hashir and Rapinder Sawhney. 2020 · 2020
Later among the works it cites.
Clinical XLNet: Modeling sequential clinical notes and predicting prolonged mechanical ventilation
Kexin Huang, Abhishek Singh, Sitong Chen, Edward Moseley, Chih-Ying Deng, Naomi George, and Charolotta Lindvall. 2020 · 2020
Later among the works it cites.
Biobert: a pre-trained biomedical language representation model for biomedical text mining
Jinhyuk Lee, Wonjin Yoon, Sungdong Kim, Donghyeon Kim, Sunkyu Kim, Chan Ho So, and Jaewoo Kang. 2020 · 2020
Later among the works it cites.
Automated assessment and tracking of covid-19 pulmonary disease severity on chest radiographs using convolutional siamese neural networks
Matthew D Li, Nishanth Thumbavanam Arun, Mishka Gidwani, Ken Chang, Francis Deng, Brent P Little, Dexter P Mendoza, Min Lang, Susanna I Lee, Aileen O’Shea, et al. 2020 · 2020
Later among the works it cites.
MSˆ2: Multi-document summarization of medical studies
Jay DeYoung, Iz Beltagy, Madeleine van Zuylen, Bailey Kuehl, and Lucy Wang. 2021 · 2021
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Latent retrieval for weakly supervised open domain question answering
Kenton Lee, Ming-Wei Chang, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
Inferring which medical treatments work from reports of clinical trials
Eric Lehman, Jay DeYoung, Regina Barzilay, and Byron C Wallace. 2019 · 2019
Cited alongside, same era.
ScispaCy: Fast and robust models for biomedical natural language processing
Mark Neumann, Daniel King, Iz Beltagy, and Waleed Ammar. 2019 · 2019
Cited alongside, same era.
Transfer learning in biomedical natural language processing: An evaluation of bert and elmo on ten benchmarking datasets
Yifan Peng, Shankai Yan, and Zhiyong Lu. 2019 · 2019
Cited alongside, same era.
What does the evidence say? models to help make sense of the biomedical literature
Byron C Wallace. 2019 · 2019
Cited alongside, same era.
Sequence-to-set semantic tagging for complex query reformulation and automated text categorization in biomedical IR using self-attention
Manirupa Das, Juanxi Li, Eric Fosler-Lussier, Simon Lin, Steve Rust, Yungui Huang, and Rajiv Ramnath. 2020 · 2020
Cited alongside, same era.
Evidence inference 2.0: More data, better models
Jay DeYoung, Eric Lehman, Benjamin Nye, Iain Marshall, and Byron C Wallace. 2020 · 2020
Cited alongside, same era.
Closest in time.
Launching into clinical space with medspacy: a new clinical text processing toolkit in python
Hannah Eyre, Alec B Chapman, Kelly S Peterson, Jianlin Shi, Patrick R Alba, Makoto M Jones, Tamara L Box, Scott L DuVall, and Olga V Patterson. 2021 · 2021
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Complement lexical retrieval model with semantic residual embeddings
Luyu Gao, Zhuyun Dai, Tongfei Chen, Zhen Fan, Benjamin Van Durme, and Jamie Callan. 2021 · 2021
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Domain-specific language model pretraining for biomedical natural language processing
Yu Gu, Robert Tinn, Hao Cheng, Michael Lucas, Naoto Usuyama, Xiaodong Liu, Tristan Naumann, Jianfeng Gao, and Hoifung Poon. 2021 · 2021
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UmlsBERT: Clinical domain knowledge augmentation of contextual embeddings using the Unified Medical Language System Metathesaurus
George Michalopoulos, Yuanxin Wang, Hussam Kaka, Helen Chen, and Alexander Wong. 2021 · 2021
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Clinical outcome prediction from admission notes using self-supervised knowledge integration
Betty van Aken, Jens-Michalis Papaioannou, Manuel Mayrdorfer, Klemens Budde, Felix Gers, and Alexander Loeser. 2021 · 2021
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Trec-covid: constructing a pandemic information retrieval test collection
Ellen Voorhees, Tasmeer Alam, Steven Bedrick, Dina Demner-Fushman, William R Hersh, Kyle Lo, Kirk Roberts, Ian Soboroff, and Lucy Lu Wang. 2021 · 2021
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Domain-specific pretraining for vertical search: Case study on biomedical literature
Yu Wang, Jinchao Li, Tristan Naumann, Chenyan Xiong, Hao Cheng, Robert Tinn, Cliff Wong, Naoto Usuyama, Richard Rogahn, Zhihong Shen, et al. 2021 · 2021
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Structured fine-tuning of contextual embeddings for effective biomedical retrieval
Alberto Ueda, Rodrygo L. T. Santos, Craig Macdonald, and Iadh Ounis. 2021 · 2035
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