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We introduce NoteChat, a novel cooperative multi-agent framework leveraging Large Language Models (LLMs) to generate patient-physician dialogues.
Language models are few-shot learners
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Hipaa regulations: a new era of medical-record privacy?
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Generating soap notes from doctor-patient conversations using modular summarization techniques
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Cooperative multi-agent learning: The state of the art
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Quality, cost, and value of clinical skills assessment
Lewis R First, Humayun J Chaudhry, and Donald E Melnick. 2013 · 2013
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Means: A medical question-answering system combining nlp techniques and semantic web technologies
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Quickumls: a fast, unsupervised approach for medical concept extraction
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Meddialog: Large-scale medical dialogue datasets
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Training verifiers to solve math word problems
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Launching into clinical space with medspaCy: a new clinical text processing toolkit in Python
H. Eyre, A. B. Chapman, K. S. Peterson, J. Shi, P. R. Alba, M. M. Jones, T. L. Box, S. L. DuVall, and O. V. Patterson. 2021 · 2021
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Enriching contextualized language model from knowledge graph for biomedical information extraction
Hao Fei, Yafeng Ren, Yue Zhang, Donghong Ji, and Xiaohui Liang. 2021 · 2021
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Discourse understanding and factual consistency in abstractive summarization
Saadia Gabriel, Antoine Bosselut, Jeff Da, Ari Holtzman, Jan Buys, Kyle Lo, Asli Celikyilmaz, and Yejin Choi. 2021 · 2021
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Soap notes.[updated 2021 sep 2]
V Podder, V Lew, and S Ghassemzadeh. 2021 · 2021
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The past, present, and future of the united states medical licensing examination step 2 clinical skills examination
Jason T Tsichlis, Andrew M Del Re, and J Bryan Carmody. 2021 · 2021
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Improving formality style transfer with context-aware rule injection
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Towards automating medical scribing: Clinic visit dialogue2note sentence alignment and snippet summarization
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How does chatgpt perform on the united states medical licensing examination? the implications of large language models for medical education and knowledge assessment
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A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions
Lei Huang, Weijiang Yu, Weitao Ma, Weihong Zhong, Zhangyin Feng, Haotian Wang, Qianglong Chen, Weihua Peng, Xiaocheng Feng, Bing Qin, and Ting Liu. 2023 · 2023
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The flan collection: Designing data and methods for effective instruction tuning
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Synthetic imitation edit feedback for factual alignment in clinical summarization
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Sunjae Kwon, Zonghai Yao, Harmon S Jordan, David A Levy, Brian Corner, and Hong Yu. 2022 · 2022
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Faithful or extractive? on mitigating the faithfulness-abstractiveness trade-off in abstractive summarization
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Secure multiparty computation for synthetic data generation from distributed data
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Patterns in physician burnout in a stable-linked cohort
Marcus V Ortega, Michael K Hidrue, Sara R Lehrhoff, Dan B Ellis, Rachel C Sisodia, William T Curry, Marcela G Del Carmen, and Jason H Wasfy. 2023 · 2023
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Generating more faithful and consistent soap notes using attribute-specific parameters
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Llama: Open and efficient foundation language models
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Improving summarization with human edits
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Aci-bench: a novel ambient clinical intelligence dataset for benchmarking automatic visit note generation
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Causality-aware concept extraction based on knowledge-guided prompting
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Chatdoctor: A medical chat model fine-tuned on llama model using medical domain knowledge
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Huatuogpt, towards taming language models to be a doctor
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Judging llm-as-a-judge with mt-bench and chatbot arena
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric. P Xing, Hao Zhang, Joseph E. Gonzalez, and Ion Stoica. 2023 · 2023
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