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This paper presents our contribution to the MEDIQA-2023 Dialogue2Note shared task, encompassing both subtask A and subtask B.
Publicly available clinical bert embeddings
Emily Alsentzer, John R Murphy, Willie Boag, Wei-Hung Weng, Di Jin, Tristan Naumann, and Matthew McDermott. 2019 · 1904
Earlier work this paper cites.
Clinicalbert: Modeling clinical notes and predicting hospital readmission
Kexin Huang, Jaan Altosaar, and Rajesh Ranganath. 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
Earlier work this paper cites.
Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
Earlier work this paper cites.
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Ves Stoyanov, and Luke Zettlemoyer. 2019 · 1910
Earlier work this paper cites.
SciBERT: A pretrained language model for scientific text
Iz Beltagy, Kyle Lo, and Arman Cohan. 2019 · 2019
Earlier work this paper cites.
Enhancing clinical concept extraction with contextual embeddings
Yuqi Si, Jingqi Wang, Hua Xu, and Kirk Roberts. 2019 · 2019
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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
Earlier work this paper cites.
Identifying relevant information in medical conversations to summarize a clinician-patient encounter
Juan C Quiroz, Liliana Laranjo, Ahmet Baki Kocaballi, Agustina Briatore, Shlomo Berkovsky, Dana Rezazadegan, and Enrico Coiera. 2020 · 2020
Earlier work this paper cites.
Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu. 2020 · 2020
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BLEURT: Learning robust metrics for text generation
Thibault Sellam, Dipanjan Das, and Ankur Parikh. 2020 · 2020
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Pegasus: Pre-training with extracted gap-sentences for abstractive summarization
Jingqing Zhang, Yao Zhao, Mohammad Saleh, and Peter Liu. 2020 · 2020
Cited alongside, same era.
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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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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Medicalsum: A guided clinical abstractive summarization model for generating medical reports from patient-doctor conversations
George Michalopoulos, Kyle Williams, Gagandeep Singh, and Thomas Lin. 2022 · 2022
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Few-shot fine-tuning sota summarization models for medical dialogues
David Fraile Navarro, Mark Dras, and Shlomo Berkovsky. 2022 · 2022
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Investigating crowdsourcing protocols for evaluating the factual consistency of summaries
Xiangru Tang, Alexander Fabbri, Haoran Li, Ziming Mao, Griffin Adams, Borui Wang, Asli Celikyilmaz, Yashar Mehdad, and Dragomir Radev. 2022a · 2022
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CONFIT: Toward faithful dialogue summarization with linguistically-informed contrastive fine-tuning
Xiangru Tang, Arjun Nair, Borui Wang, Bingyao Wang, Jai Desai, Aaron Wade, Haoran Li, Asli Celikyilmaz, Yashar Mehdad, and Dragomir Radev. 2022b · 2022
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Overview of the mediqa-chat 2023 shared tasks on the summarization and generation of doctor-patient conversations
Asma Ben Abacha, Wen wai Yim, Griffin Adams, Neal Snider, and Meliha Yetisgen. 2023a · 2023
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A survey for in-context learning
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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. 2023b · 2023
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Evaluating large language models on medical evidence summarization
Liyan Tang, Zhaoyi Sun, Betina Idnay, Jordan G Nestor, Ali Soroush, Pierre A Elias, Ziyang Xu, Ying Ding, Greg Durrett, Justin Rousseau, et al. 2023a · 2023
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Aligning factual consistency for clinical studies summarization through reinforcement learning
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The aci demo corpus: An open dataset for benchmarking the state-of-the-art for automatic note generation from doctor-patient conversations
Wen wai Yim, Yujuan Fu, Asma Ben Abacha, Neal Snider, Thomas Lin, and Meliha Yetisgen. 2023 · 2023
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