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Long-form clinical summarization of hospital admissions has real-world significance because of its potential to help both clinicians and patients.
Transformer-xl: Attentive language models beyond a fixed-length context
Zihang Dai, Zhilin Yang, Yiming Yang, Jaime Carbonell, Quoc V Le, and Ruslan Salakhutdinov. 2019 · 1901
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Publicly available clinical bert embeddings
Emily Alsentzer, John R Murphy, Willie Boag, Wei-Hung Weng, Di Jin, Tristan Naumann, and Matthew McDermott. 2019b · 1904
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The curious case of neural text degeneration
Ari Holtzman, Jan Buys, Li Du, Maxwell Forbes, and Yejin Choi. 2019 · 1904
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Bertscore: Evaluating text generation with bert
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q Weinberger, and Yoav Artzi. 2019 · 1904
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On faithfulness and factuality in abstractive summarization
Joshua Maynez, Shashi Narayan, Bernd Bohnet, and Ryan McDonald. 2020 · 1919
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Using lexical chains for text summarization
Regina Barzilay and Michael Elhadad. 1997 · 1997
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Effect of discharge summary availability during post-discharge visits on hospital readmission
Carl Van Walraven, Ratika Seth, Peter C Austin, and Andreas Laupacis. 2002 · 2002
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Towards patient record summarization through joint phenotype learning in hiv patients
Gal Levy-Fix, Jason Zucker, Konstantin Stojanovic, and Noémie Elhadad. 2020 · 2003
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Longformer: The long-document transformer
Iz Beltagy, Matthew E Peters, and Arman Cohan. 2020 · 2004
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The unified medical language system (umls): integrating biomedical terminology
Olivier Bodenreider. 2004 · 2004
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Copy-and-paste
Robert E Hirschtick. 2006 · 2006
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Deficits in communication and information transfer between hospital-based and primary care physicians: implications for patient safety and continuity of care
Sunil Kripalani, Frank LeFevre, Christopher O Phillips, Mark V Williams, Preetha Basaviah, and David W Baker. 2007 · 2007
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Documentation of mandated discharge summary components in transitions from acute to subacute care
Amy JH Kind and Maureen A Smith. 2008 · 2008
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Pearson correlation coefficient
Israel Cohen, Yiteng Huang, Jingdong Chen, Jacob Benesty, Jacob Benesty, Jingdong Chen, Yiteng Huang, and Israel Cohen. 2009 · 2009
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Creating a better discharge summary: improvement in quality and timeliness using an electronic discharge summary
Kevin J O’Leary, David M Liebovitz, Joseph Feinglass, David T Liss, Daniel B Evans, Nita Kulkarni, Matthew P Landler, and David W Baker. 2009 · 2009
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Improving the efficiency of discharge summary completion by linking to preexisiting patient information databases
Samuel Chan, Andrew P Maurice, Clifford W Pollard, Stephen J Ayre, Darren L Walters, and Helen E Ward. 2014 · 2014
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Testing for significance of increased correlation with human judgment
Yvette Graham and Timothy Baldwin. 2014 · 2014
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On evaluation of automatically generated clinical discharge summaries
Hans Moen, Juho Heimonen, Laura-Maria Murtola, Antti Airola, Tapio Pahikkala, Virpi Terävä, Riitta Danielsson-Ojala, Tapio Salakoski, and Sanna Salanterä. 2014 · 2014
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A large annotated corpus for learning natural language inference
Samuel R. Bowman, Gabor Angeli, Christopher Potts, and Christopher D. Manning. 2015 · 2015
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Teaching machines to read and comprehend
Karl Moritz Hermann, Tomás Kociský, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, and Phil Blunsom. 2015 · 2015
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Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean. 2015 · 2015
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Understanding the burnout experience: recent research and its implications for psychiatry
Christina Maslach and Michael P Leiter. 2016 · 2016
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Relationship between clerical burden and characteristics of the electronic environment with physician burnout and professional satisfaction
Tait D Shanafelt, Lotte N Dyrbye, Christine Sinsky, Omar Hasan, Daniel Satele, Jeff Sloan, and Colin P West. 2016 · 2016
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Allocation of physician time in ambulatory practice: a time and motion study in 4 specialties
Christine Sinsky, Lacey Colligan, Ling Li, Mirela Prgomet, Sam Reynolds, Lindsey Goeders, Johanna Westbrook, Michael Tutty, and George Blike. 2016 · 2016
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Comorbidities among us patients with prevalent hiv infection—a trend analysis
Joel Gallant, Priscilla Y Hsue, Sanatan Shreay, and Nicole Meyer. 2017 · 2017
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Physical, psychological and occupational consequences of job burnout: A systematic review of prospective studies
Denise Albieri Jodas Salvagioni, Francine Nesello Melanda, Arthur Eumann Mesas, Alberto Durán González, Flávia Lopes Gabani, and Selma Maffei de Andrade. 2017 · 2017
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Get to the point: Summarization with pointer-generator networks
Abigail See, Peter J. Liu, and Christopher D. Manning. 2017 · 2017
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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 · 2017
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Newsroom: A dataset of 1.3 million summaries with diverse extractive strategies
Max Grusky, Mor Naaman, and Yoav Artzi. 2018 · 2018
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Don’t give me the details, just the summary! topic-aware convolutional neural networks for extreme summarization
Shashi Narayan, Shay B. Cohen, and Mirella Lapata. 2018 · 2018
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Association between physician burnout and patient safety, professionalism, and patient satisfaction: a systematic review and meta-analysis
Maria Panagioti, Keith Geraghty, Judith Johnson, Anli Zhou, Efharis Panagopoulou, Carolyn Chew-Graham, David Peters, Alexander Hodkinson, Ruth Riley, and Aneez Esmail. 2018 · 2018
Cited alongside, same era.
Lessons from natural language inference in the clinical domain
Alexey Romanov and Chaitanya Shivade. 2018 · 2018
Cited alongside, same era.
Clamp–a toolkit for efficiently building customized clinical natural language processing pipelines
Ergin Soysal, Jingqi Wang, Min Jiang, Yonghui Wu, Serguei Pakhomov, Hongfang Liu, and Hua Xu. 2018 · 2018
Cited alongside, same era.
Ranking generated summaries by correctness: An interesting but challenging application for natural language inference
Tobias Falke, Leonardo F. R. Ribeiro, Prasetya Ajie Utama, Ido Dagan, and Iryna Gurevych. 2019 · 2019
Cited alongside, same era.
Assessing the factual accuracy of generated text
Ben Goodrich, Vinay Rao, Peter J Liu, and Mohammad Saleh. 2019 · 2019
Improving zero and few-shot abstractive summarization with intermediate fine-tuning and data augmentation
Alexander Fabbri, Simeng Han, Haoyuan Li, Haoran Li, Marjan Ghazvininejad, Shafiq Joty, Dragomir Radev, and Yashar Mehdad. 2021a · 2021
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Annotating and modeling fine-grained factuality in summarization
Tanya Goyal and Greg Durrett. 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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Longt5: Efficient text-to-text transformer for long sequences
Mandy Guo, Joshua Ainslie, David Uthus, Santiago Ontanon, Jianmo Ni, Yun-Hsuan Sung, and Yinfei Yang. 2021 · 2021
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Self-alignment pretraining for biomedical entity representations
Fangyu Liu, Ehsan Shareghi, Zaiqiao Meng, Marco Basaldella, and Nigel Collier. 2021 · 2021
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Cited alongside, same era.
Association of electronic health record design and use factors with clinician stress and burnout
Philip J Kroth, Nancy Morioka-Douglas, Sharry Veres, Stewart Babbott, Sara Poplau, Fares Qeadan, Carolyn Parshall, Kathryne Corrigan, and Mark Linzer. 2019 · 2019
Cited alongside, same era.
Hierarchical transformers for multi-document summarization
Yang Liu and Mirella Lapata. 2019 · 2019
Cited alongside, same era.
Ontology-aware clinical abstractive summarization
Sean MacAvaney, Sajad Sotudeh, Arman Cohan, Nazli Goharian, Ish Talati, and Ross W Filice. 2019 · 2019
Cited alongside, same era.
Taking action against clinician burnout: a systems approach to professional well-being
& Medicine & others National Academies of Sciences, Engineering. 2019 · 2019
Cited alongside, same era.
Zero-shot clinical acronym expansion via latent meaning cells
Griffin Adams, Mert Ketenci, Shreyas Bhave, Adler Perotte, and Noémie Elhadad. 2020 · 2020
Cited alongside, same era.
Re-evaluating evaluation in text summarization
Manik Bhandari, Pranav Narayan Gour, Atabak Ashfaq, Pengfei Liu, and Graham Neubig. 2020 · 2020
Cited alongside, same era.
FEQA: A question answering evaluation framework for faithfulness assessment in abstractive summarization
Esin Durmus, He He, and Mona Diab. 2020 · 2020
Cited alongside, same era.
Later among the works it cites.
Towards objectively evaluating the quality of generated medical summaries
Francesco Moramarco, Damir Juric, Aleksandar Savkov, and Ehud Reiter. 2021 · 2021
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Measurement of clinical documentation burden among physicians and nurses using electronic health records: a scoping review
Amanda J Moy, Jessica M Schwartz, RuiJun Chen, Shirin Sadri, Eugene Lucas, Kenrick D Cato, and Sarah Collins Rossetti. 2021 · 2021
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Planning with learned entity prompts for abstractive summarization
Shashi Narayan, Yao Zhao, Joshua Maynez, Gonçalo Simões, Vitaly Nikolaev, and Ryan McDonald. 2021 · 2021
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Understanding factuality in abstractive summarization with FRANK: A benchmark for factuality metrics
Artidoro Pagnoni, Vidhisha Balachandran, and Yulia Tsvetkov. 2021 · 2021
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Bartscore: Evaluating generated text as text generation
Weizhe Yuan, Graham Neubig, and Pengfei Liu. 2021 · 2021
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Learning to revise references for faithful summarization
Griffin Adams, Han-Chin Shing, Qing Sun, Christopher Winestock, Kathleen McKeown, and Noémie Elhadad. 2022b · 2022
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Hallucinated but factual! inspecting the factuality of hallucinations in abstractive summarization
Meng Cao, Yue Dong, and Jackie Cheung. 2022 · 2022
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The glass ceiling of automatic evaluation in natural language generation
Pierre Colombo, Maxime Peyrard, Nathan Noiry, Robert West, and Pablo Piantanida. 2022 · 2022
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Spurious correlations in reference-free evaluation of text generation
Esin Durmus, Faisal Ladhak, and Tatsunori Hashimoto. 2022 · 2022
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QAFactEval: Improved QA-based factual consistency evaluation for summarization
Alexander Fabbri, Chien-Sheng Wu, Wenhao Liu, and Caiming Xiong. 2022 · 2022
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News summarization and evaluation in the era of gpt-3
Tanya Goyal, Junyi Jessy Li, and Greg Durrett. 2022 · 2022
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TRUE: Re-evaluating factual consistency evaluation
Or Honovich, Roee Aharoni, Jonathan Herzig, Hagai Taitelbaum, Doron Kukliansy, Vered Cohen, Thomas Scialom, Idan Szpektor, Avinatan Hassidim, and Yossi Matias. 2022 · 2022
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Bidimensional leaderboards: Generate and evaluate language hand in hand
Jungo Kasai, Keisuke Sakaguchi, Ronan Le Bras, Lavinia Dunagan, Jacob Morrison, Alexander Fabbri, Yejin Choi, and Noah A. Smith. 2022 · 2022
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Primock57: A dataset of primary care mock consultations
Alex Papadopoulos Korfiatis, Francesco Moramarco, Radmila Sarac, and Aleksandar Savkov. 2022 · 2022
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SummaC: Re-visiting NLI-based models for inconsistency detection in summarization
Philippe Laban, Tobias Schnabel, Paul N. Bennett, and Marti A. Hearst. 2022 · 2022
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Human evaluation and correlation with automatic metrics in consultation note generation
Francesco Moramarco, Alex Papadopoulos Korfiatis, Mark Perera, Damir Juric, Jack Flann, Ehud Reiter, Anya Belz, and Aleksandar Savkov. 2022 · 2022
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Investigating efficiently extending transformers for long input summarization
Jason Phang, Yao Zhao, and Peter J Liu. 2022 · 2022
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FactGraph: Evaluating factuality in summarization with semantic graph representations
Leonardo Ribeiro, Mengwen Liu, Iryna Gurevych, Markus Dreyer, and Mohit Bansal. 2022 · 2022
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EchoGen: Generating conclusions from echocardiogram notes
Liyan Tang, Shravan Kooragayalu, Yanshan Wang, Ying Ding, Greg Durrett, Justin F. Rousseau, and Yifan Peng. 2022 · 2022
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Falsesum: Generating document-level NLI examples for recognizing factual inconsistency in summarization
Prasetya Utama, Joshua Bambrick, Nafise Moosavi, and Iryna Gurevych. 2022 · 2022
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MultiVerS: Improving scientific claim verification with weak supervision and full-document context
David Wadden, Kyle Lo, Lucy Wang, Arman Cohan, Iz Beltagy, and Hannaneh Hajishirzi. 2022 · 2022
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Self-consistency improves chain of thought reasoning in language models
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc Le, Ed Chi, and Denny Zhou. 2022 · 2022
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Chain of thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Ed Chi, Quoc Le, and Denny Zhou. 2022 · 2022
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Shiyue Zhang, David Wan, and Mohit Bansal. 2022 · 2022
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Do we still need clinical language models?
Eric Lehman, Evan Hernandez, Diwakar Mahajan, Jonas Wulff, Micah J Smith, Zachary Ziegler, Daniel Nadler, Peter Szolovits, Alistair Johnson, and Emily Alsentzer. 2023 · 2023
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