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The records of a clinical encounter can be extensive and complex, thus placing a premium on tools that can extract and summarize relevant information.
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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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Comparison of automatic summarisation methods for clinical free text notes
Hans Moen, Laura-Maria Peltonen, Juho Heimonen, Antti Airola, Tapio Pahikkala, Tapio Salakoski, and Sanna Salanterä. 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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Faithful to the original: Fact aware neural abstractive summarization
Ziqiang Cao, Furu Wei, Wenjie Li, and Sujian Li. 2017 · 2017
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The limits of automatic summarisation according to rouge
Natalie Schluter. 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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Yen-Chun Chen and Mohit Bansal. 2018 · 2018
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A novel system for extractive clinical note summarization using ehr data
Jennifer Liang, Ching-Huei Tsou, and Ananya Poddar. 2019 · 2019
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Ontology-Aware Clinical Abstractive Summarization
Sean MacAvaney, Sajad Sotudeh, Arman Cohan, Nazli Goharian, Ish Talati, and Ross W. Filice. 2019 · 2019
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ScispaCy: Fast and Robust Models for Biomedical Natural Language Processing
Mark Neumann, Daniel King, Iz Beltagy, and Waleed Ammar. 2019 · 2019
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Natural language generation for electronic health records
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Generating wikipedia by summarizing long sequences
Peter J Liu, Mohammad Saleh, Etienne Pot, Ben Goodrich, Ryan Sepassi, Lukasz Kaiser, and Noam Shazeer. 2018 · 2018
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Physician burnout, well-being, and work unit safety grades in relationship to reported medical errors
Daniel S Tawfik, Jochen Profit, Timothy I Morgenthaler, Daniel V Satele, Christine A Sinsky, Liselotte N Dyrbye, Michael A Tutty, Colin P West, and Tait D Shanafelt. 2018 · 2018
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Physician burnout: contributors, consequences and solutions
C. P. West, L. N. Dyrbye, and T. D. Shanafelt. 2018 · 2018
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Learning to Summarize Radiology Findings
Yuhao Zhang, Daisy Yi Ding, Tianpei Qian, Christopher D. Manning, and Curtis P. Langlotz. 2018 · 2018
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Guiding extractive summarization with question-answering rewards
Kristjan Arumae and Fei Liu. 2019 · 2019
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Hierarchical transformers for multi-document summarization
Yang Liu and Mirella Lapata. 2019a
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Generation and evaluation of artificial mental health records for Natural Language Processing
Julia Ive, Natalia Viani, Joyce Kam, Lucia Yin, Somain Verma, Stephen Puntis, Rudolf N. Cardinal, Angus Roberts, Robert Stewart, and Sumithra Velupillai. 2020 · 2020
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Notes and data not in mimic-iii · issue 771 · mit-lcp/mimic-code
Alistair Johnson and Chaitanya Shivade. 2020 · 2020
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Evaluating the factual consistency of abstractive text summarization
Wojciech Kryscinski, Bryan McCann, Caiming Xiong, and Richard Socher. 2020 · 2020
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Asking and answering questions to evaluate the factual consistency of summaries
Alex Wang, Kyunghyun Cho, and Mike Lewis. 2020 · 2020
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Big bird: Transformers for longer sequences
Manzil Zaheer, Guru Guruganesh, Avinava Dubey, Joshua Ainslie, Chris Alberti, Santiago Ontanon, Philip Pham, Anirudh Ravula, Qifan Wang, Li Yang, and Amr Ahmed. 2020 · 2020
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Optimizing the factual correctness of a summary: A study of summarizing radiology reports
Yuhao Zhang, Derek Merck, Emily Tsai, Christopher D. Manning, and Curtis Langlotz. 2020 · 2020
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