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Recent studies on automatic note generation have shown that doctors can save significant amounts of time when using automatic clinical note generation (Knoll et al., 2022).
Evaluating the factual consistency of abstractive text summarization
Wojciech Kryściński, Bryan McCann, Caiming Xiong, and Richard Socher. 2019 · 1910
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On faithfulness and factuality in abstractive summarization
Joshua Maynez, Shashi Narayan, Bernd Bohnet, and Ryan T. McDonald. 2020 · 1919
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The unified medical language system
Donald A. Lindberg, Betsy L. Humphreys, and Alexa T. McCray. 1993 · 1993
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The unified medical language system (umls): integrating biomedical terminology
Olivier Bodenreider. 2004 · 2004
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Looking for a few good metrics: Automatic summarization evaluation - how many samples are enough?
Chin-Yew Lin. 2004a · 2004
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Healthcare Informatics: Improving Efficiency and Productivity
Stephan Kudyba. 2010 · 2010
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An assessment of the accuracy of automatic evaluation in summarization
Karolina Owczarzak, John M. Conroy, Hoa Trang Dang, and Ani Nenkova. 2012 · 2012
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Re-evaluating automatic summarization with BLEU and 192 shades of ROUGE
Yvette Graham. 2015 · 2015
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Tethered to the ehr: Primary care physician workload assessment using ehr event log data and time-motion observations
Brian G. Arndt, John W. Beasley, Michelle D. Watkinson, Jonathan L. Temte, Wen-Jan Tuan, Christine A. Sinsky, and Valerie J. Gilchrist. 2017 · 2017
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KBGAN: adversarial learning for knowledge graph embeddings
Liwei Cai and William Yang Wang. 2018 · 2018
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Using voice to create hospital progress notes: Description of a mobile application and supporting system integrated with a commercial electronic health record
Thomas H. Payne, W. David Alonso, J. Andrew Markiel, Kevin Lybarger, and Andrew A. White. 2018 · 2018
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Highres: Highlight-based reference-less evaluation of summarization
Hardy, Shashi Narayan, and Andreas Vlachos. 2019 · 2019
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Large-scale, diverse, paraphrastic bitexts via sampling and clustering
J. Edward Hu, Abhinav Singh, Nils Holzenberger, Matt Post, and Benjamin Van Durme. 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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Studying summarization evaluation metrics in the appropriate scoring range
Maxime Peyrard. 2019 · 2019
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MoverScore: Text generation evaluating with contextualized embeddings and earth mover distance
Wei Zhao, Maxime Peyrard, Fei Liu, Yang Gao, Christian M. Meyer, and Steffen Eger. 2019 · 2019
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Re-evaluating evaluation in text summarization
Manik Bhandari, Pranav Narayan Gour, Atabak Ashfaq, Pengfei Liu, and Graham Neubig. 2020 · 2020
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FEQA: A question answering evaluation framework for faithfulness assessment in abstractive summarization
Esin Durmus, He He, and Mona T. Diab. 2020 · 2020
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Deberta: Decoding-enhanced bert with disentangled attention
Pengcheng He, Xiaodong Liu, Jianfeng Gao, and Weizhu Chen. 2021 · 2021
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Multi-domain clinical natural language processing with MedCAT: The medical concept annotation toolkit
Zeljko Kraljevic, Thomas Searle, Anthony Shek, Lukasz Roguski, Kawsar Noor, Daniel Bean, Aurelie Mascio, Leilei Zhu, Amos A Folarin, Angus Roberts, Rebecca Bendayan, Mark P Richardson, Robert Stewart, Anoop D Shah, Wai Keong Wong, Zina Ibrahim, James T Teo, and Richard J B Dobson. 2021 · 2021
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Generating SOAP notes from doctor-patient conversations using modular summarization techniques
Kundan Krishna, Sopan Khosla, Jeffrey Bigham, and Zachary C. Lipton. 2021 · 2021
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Improving factual consistency of abstractive summarization via question answering
Feng Nan, Cícero Nogueira dos Santos, Henghui Zhu, Patrick Ng, Kathleen R. McKeown, Ramesh Nallapati, Dejiao Zhang, Zhiguo Wang, Andrew O. Arnold, and Bing Xiang. 2021 · 2021
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Understanding factuality in abstractive summarization with FRANK: A benchmark for factuality metrics
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Seppo Enarvi, Marilisa Amoia, Miguel Del-Agua Teba, Brian Delaney, Frank Diehl, Stefan Hahn, Kristina Harris, Liam McGrath, Yue Pan, Joel Pinto, Luca Rubini, Miguel Ruiz, Gagandeep Singh, Fabian Stemmer, Weiyi Sun, Paul Vozila, Thomas Lin, and Ranjani Ramamurthy. 2020 · 2020
Cited alongside, same era.
Twenty years of confusion in human evaluation: NLG needs evaluation sheets and standardised definitions
David M. Howcroft, Anya Belz, Miruna-Adriana Clinciu, Dimitra Gkatzia, Sadid A Hasan, Saad Mahamood, Simon Mille, Emiel van Miltenburg, Sashank Santhanam, and Verena Rieser. 2020 · 2020
Cited alongside, same era.
BART: denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer. 2020 · 2020
Cited alongside, same era.
BLEURT: learning robust metrics for text generation
Thibault Sellam, Dipanjan Das, and Ankur P. Parikh. 2020 · 2020
Cited alongside, same era.
Asking and answering questions to evaluate the factual consistency of summaries
Alex Wang, Kyunghyun Cho, and Mike Lewis. 2020 · 2020
Cited alongside, same era.
Bertscore: Evaluating text generation with bert
Tianyi Zhang*, Varsha Kishore*, Felix Wu*, Kilian Q. Weinberger, and Yoav Artzi. 2020 · 2020
Cited alongside, same era.
Overview of the MEDIQA 2021 shared task on summarization in the medical domain
Asma Ben Abacha, Yassine Mrabet, Yuhao Zhang, Chaitanya Shivade, Curtis P. Langlotz, and Dina Demner-Fushman. 2021 · 2021
Cited alongside, same era.
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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Generation of patient after-visit summaries to support physicians
Pengshan Cai, Fei Liu, Adarsha Bajracharya, Joe Sills, Alok Kapoor, Weisong Liu, Dan Berlowitz, David Levy, Richeek Pradhan, and Hong Yu. 2022 · 2022
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Re-examining system-level correlations of automatic summarization evaluation metrics
Daniel Deutsch, Rotem Dror, and Dan Roth. 2022 · 2022
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User-driven research of medical note generation software
Tom Knoll, Francesco Moramarco, Alex Papadopoulos Korfiatis, Rachel Young, Claudia Ruffini, Mark Perera, Christian Perstl, Ehud Reiter, Anya Belz, and Aleksandar Savkov. 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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Shiyue Zhang, David Wan, and Mohit Bansal. 2022 · 2022
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An empirical study of clinical note generation from doctor-patient encounters
Asma Ben Abacha, Wen-wai Yim, Yadan Fan, and Thomas Lin. 2023 · 2023
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