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Large language models (LLMs) have demonstrated significant potential in clinical decision support.
K-bert: Enabling language representation with knowledge graph, 2019
Weijie Liu, Peng Zhou, Zhe Zhao, Zhiruo Wang, Qi Ju, Haotang Deng, and Ping Wang · 1909
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Receiver-operating characteristic (roc) plots: a fundamental evaluation tool in clinical medicine
Mark H Zweig and Gregory Campbell · 1993
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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The unified medical language system (umls): integrating biomedical terminology
Olivier Bodenreider · 2004
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Retrieval-augmented generation for knowledge-intensive nlp tasks, 2021
Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen tau Yih, Tim Rocktäschel, Sebastian Riedel, and Douwe Kiela · 2005
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Community detection in graphs
Santo Fortunato · 2010
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Modern hierarchical, agglomerative clustering algorithms
Daniel Müllner · 2011
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Pubmed: the bibliographic database
Kathi Canese and Sarah Weis · 2013
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Empirical evaluation of gated recurrent neural networks on sequence modeling
Junyoung Chung, Caglar Gulcehre, KyungHyun Cho, and Yoshua Bengio · 2014
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Real-time prediction of mortality, readmission, and length of stay using electronic health record data
X Cai, O Perez-Concha, E Coiera, F Martin-Sanchez, R Day, D Roffe, and B Gallego · 2015
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Retain: An interpretable predictive model for healthcare using reverse time attention mechanism
Edward Choi, Mohammad Taha Bahadori, Jimeng Sun, Joshua Kulas, Andy Schuetz, and Walter Stewart · 2016
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Mimic-iii, a freely accessible critical care database
Alistair EW Johnson, Tom J Pollard, Lu Shen, Li-wei H Lehman, Mengling Feng, Mohammad Ghassemi, Benjamin Moody, Peter Szolovits, Leo Anthony Celi, and Roger G Mark · 2016
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Deepr: a convolutional net for medical records
Phuoc Nguyen, Truyen Tran, Nilmini Wickramasinghe, and Svetha Venkatesh · 2016
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Gram: graph-based attention model for healthcare representation learning
Edward Choi, Mohammad Taha Bahadori, Le Song, Walter F Stewart, and Jimeng Sun · 2017
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Deep ehr: A survey of recent advances in deep learning techniques for electronic health record (ehr) analysis
Benjamin Shickel, Patrick James Tighe, Azra Bihorac, and Parisa Rashidi · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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An empirical evaluation of generic convolutional and recurrent networks for sequence modeling
Shaojie Bai, J Zico Kolter, and Vladlen Koltun · 2018
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Mime: Multilevel medical embedding of electronic health records for predictive healthcare, 2018
Edward Choi, Cao Xiao, Walter F. Stewart, and Jimeng Sun · 2018
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Scikit-learn: Machine learning in python, 2018
Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Andreas Müller, Joel Nothman, Gilles Louppe, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, Jake Vanderplas, Alexandre Passos, David Cournapeau, Matthieu Brucher, Matthieu Perrot, and Édouard Duchesnay · 2018
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Readmission prediction using deep learning on electronic health records
Awais Ashfaq, Anita Sant’Anna, Markus Lingman, and Sławomir Nowaczyk · 2019
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Graspy: Graph statistics in python
Jaewon Chung, Benjamin D Pedigo, Eric W Bridgeford, Bijan K Varjavand, Hayden S Helm, and Joshua T Vogelstein · 2019
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Gravity-inspired graph autoencoders for directed link prediction
Guillaume Salha, Stratis Limnios, Romain Hennequin, Viet-Anh Tran, and Michalis Vazirgiannis · 2019
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From louvain to leiden: guaranteeing well-connected communities
Vincent A Traag, Ludo Waltman, and Nees Jan Van Eck · 2019
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Stagenet: Stage-aware neural networks for health risk prediction
Junyi Gao, Cao Xiao, Yasha Wang, Wen Tang, Lucas M Glass, and Jimeng Sun · 2020
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Mimic-iv
Alistair Johnson, Lucas Bulgarelli, Tom Pollard, Steven Horng, Leo Anthony Celi, and Roger Mark · 2020
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Evaluation: from precision, recall and f-measure to roc, informedness, markedness and correlation
David MW Powers · 2020
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Deepspeed: System optimizations enable training deep learning models with over 100 billion parameters
Seqcare: Sequential training with external medical knowledge graph for diagnosis prediction in healthcare data
Yongxin Xu, Xu Chu, Kai Yang, Zhiyuan Wang, Peinie Zou, Hongxin Ding, Junfeng Zhao, Yasha Wang, and Bing Xie · 2023
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PyHealth: A deep learning toolkit for healthcare predictive modeling
Chaoqi Yang, Zhenbang Wu, Patrick Jiang, Zhen Lin, Junyi Gao, Benjamin Danek, and Jimeng Sun · 2023
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Introducing claude 3.5 sonnet
Anthropic · 2024
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A systematic review of testing and evaluation of healthcare applications of large language models (llms)
Suhana Bedi, Yutong Liu, Lucy Orr-Ewing, Dev Dash, Sanmi Koyejo, Alison Callahan, Jason A. Fries, Michael Wornow, Akshay Swaminathan, Lisa Soleymani Lehmann, Hyo Jung Hong, Mehr Kashyap, Akash R. Chaurasia, Nirav R. Shah, Karandeep Singh, Troy Tazbaz, Arnold Milstein, Michael A. Pfeffer, and Nigam H. Shah · 2024
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Clinicalbench: Can llms beat traditional ml models in clinical prediction?, 2024
Canyu Chen, Jian Yu, Shan Chen, Che Liu, Zhongwei Wan, Danielle Bitterman, Fei Wang, and Kai Shu · 2024
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Jeff Rasley, Samyam Rajbhandari, Olatunji Ruwase, and Yuxiong He · 2020
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Cluster quality analysis using silhouette score
Ketan Rajshekhar Shahapure and Charles Nicholas · 2020
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Trl: Transformer reinforcement learning
Leandro von Werra, Younes Belkada, Lewis Tunstall, Edward Beeching, Tristan Thrush, Nathan Lambert, Shengyi Huang, Kashif Rasul, and Quentin Gallouédec · 2020
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Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander M. Rush · 2020
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Personalizing medication recommendation with a graph-based approach
Suman Bhoi, Mong Li Lee, Wynne Hsu, Hao Sen Andrew Fang, and Ngiap Chuan Tan · 2021
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A survey of community detection approaches: From statistical modeling to deep learning
Di Jin, Zhizhi Yu, Pengfei Jiao, Shirui Pan, Dongxiao He, Jia Wu, S Yu Philip, and Weixiong Zhang · 2021
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Medretriever: Target-driven interpretable health risk prediction via retrieving unstructured medical text
Muchao Ye, Suhan Cui, Yaqing Wang, Junyu Luo, Cao Xiao, and Fenglong Ma · 2021
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Tri Dao · 2024
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Potential of large language models in health care: Delphi study
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From local to global: A graph rag approach to query-focused summarization
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Knowledge-augmented reasoning distillation for small language models in knowledge-intensive tasks
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Yubin Kim, Xuhai Xu, Daniel McDuff, Cynthia Breazeal, and Hae Won Park · 2024
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Large language models are clinical reasoners: Reasoning-aware diagnosis framework with prompt-generated rationales
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