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The development of large language models tailored for handling patients' clinical notes is often hindered by the limited accessibility and usability of these notes due to strict privacy regulations.
Language models are few-shot learners
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What can natural language processing do for clinical decision support?
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Cohort profile of the south london and maudsley nhs foundation trust biomedical research centre (slam brc) case register: current status and recent enhancement of an electronic mental health record-derived data resource
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Attention is all you need
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2018 n2c2 shared task on adverse drug events and medication extraction in electronic health records
Sam Henry, Kevin Buchan, Michele Filannino, Amber Stubbs, and Ozlem Uzuner. 2020 · 2018
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Publicly available clinical bert embeddings
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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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Towards automatic generation of shareable synthetic clinical notes using neural language models
Oren Melamud and Chaitanya Shivade. 2019 · 2019
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Language models are unsupervised multitask learners
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Generation and evaluation of artificial mental health records for natural language processing
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Rethinking domain adaptation for machine learning over clinical language
Egoitz Laparra, Steven Bethard, and Timothy A Miller. 2020 · 2020
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Pretrained language models for biomedical and clinical tasks: understanding and extending the state-of-the-art
Patrick Lewis, Myle Ott, Jingfei Du, and Veselin Stoyanov. 2020 · 2020
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Are synthetic clinical notes useful for real natural language processing tasks: A case study on clinical entity recognition
Jianfu Li, Yujia Zhou, Xiaoqian Jiang, Karthik Natarajan, Serguei Vs Pakhomov, Hongfang Liu, and Hua Xu. 2021 · 2021
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Large language models are few-shot clinical information extractors
Monica Agrawal, Stefan Hegselmann, Hunter Lang, Yoon Kim, and David Sontag. 2022 · 2022
Medalpaca–an open-source collection of medical conversational ai models and training data
Tianyu Han, Lisa C Adams, Jens-Michalis Papaioannou, Paul Grundmann, Tom Oberhauser, Alexander Löser, Daniel Truhn, and Keno K Bressem. 2023 · 2023
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Zero-shot clinical entity recognition using chatgpt
Yan Hu, Iqra Ameer, Xu Zuo, Xueqing Peng, Yujia Zhou, Zehan Li, Yiming Li, Jianfu Li, Xiaoqian Jiang, and Hua Xu. 2023 · 2023
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Chatgpt for healthcare services: An emerging stage for an innovative perspective
Mohd Javaid, Abid Haleem, and Ravi Pratap Singh. 2023 · 2023
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Survey of hallucination in natural language generation
Ziwei Ji, Nayeon Lee, Rita Frieske, Tiezheng Yu, Dan Su, Yan Xu, Etsuko Ishii, Ye Jin Bang, Andrea Madotto, and Pascale Fung. 2023 · 2023
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Mimic-iv-note: Deidentified free-text clinical notes
Alistair Johnson, Tom Pollard, Steven Horng, Leo Anthony Celi, and Roger Mark. 2023 · 2023
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FlashAttention: Fast and memory-efficient exact attention with IO-awareness
Tri Dao, Daniel Y. Fu, Stefano Ermon, Atri Rudra, and Christopher Ré. 2022 · 2022
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Tasks as needs: reframing the paradigm of clinical natural language processing research for real-world decision support
Asher Lederman, Reeva Lederman, and Karin Verspoor. 2022 · 2022
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Learning to ask like a physician
Eric Lehman, Vladislav Lialin, Katelyn Edelwina Legaspi, Anne Janelle Sy, Patricia Therese Pile, Nicole Rose Alberto, Richard Raymund Ragasa, Corinna Victoria Puyat, Marianne Katharina Taliño, Isabelle Rose Alberto, et al. 2022 · 2022
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Can large language models reason about medical questions?
Valentin Liévin, Christoffer Egeberg Hother, and Ole Winther. 2022 · 2022
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Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al. 2022 · 2022
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A survey on clinical natural language processing in the united kingdom from 2007 to 2022
Honghan Wu, Minhong Wang, Jinge Wu, Farah Francis, Yun-Hsuan Chang, Alex Shavick, Hang Dong, Michael TC Poon, Natalie Fitzpatrick, Adam P Levine, et al. 2022 · 2022
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A large language model for electronic health records
Xi Yang, Aokun Chen, Nima PourNejatian, Hoo Chang Shin, Kaleb E Smith, Christopher Parisien, Colin Compas, Cheryl Martin, Anthony B Costa, Mona G Flores, et al. 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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A comparative study of pretrained language models for long clinical text
Yikuan Li, Ramsey M Wehbe, Faraz S Ahmad, Hanyin Wang, and Yuan Luo. 2023 · 2023
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Harsha Nori, Nicholas King, Scott Mayer McKinney, Dean Carignan, and Eric Horvitz. 2023 · 2023
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OpenAI. 2023 · 2023
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Evaluating large language models on medical evidence summarization
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Stanford alpaca: An instruction-following llama model
Rohan Taori, Ishaan Gulrajani, Tianyi Zhang, Yann Dubois, Xuechen Li, Carlos Guestrin, Percy Liang, and Tatsunori B. Hashimoto. 2023 · 2023
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Augustin Toma, Patrick R Lawler, Jimmy Ba, Rahul G Krishnan, Barry B Rubin, and Bo Wang. 2023 · 2023
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Llama: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, et al. 2023 · 2023
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Self-instruct: Aligning language models with self-generated instructions
Yizhong Wang, Yeganeh Kordi, Swaroop Mishra, Alisa Liu, Noah A. Smith, Daniel Khashabi, and Hannaneh Hajishirzi. 2023 · 2023
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Chatdoctor: A medical chat model fine-tuned on llama model using medical domain knowledge
Li Yunxiang, Li Zihan, Zhang Kai, Dan Ruilong, and Zhang You. 2023 · 2023
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Zhengyun Zhao, Qiao Jin, Fangyuan Chen, Tuorui Peng, and Sheng Yu. 2023 · 2023
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