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Clinical trial matching is a key process in health delivery and discovery.
EliXR: an approach to eligibility criteria extraction and representation
Chunhua Weng, Xiaoying Wu, Zhihui Luo, Mary Regina Boland, Dimitri Theodoratos, and Stephen B Johnson · 2011
Earlier work this paper cites.
tmvar: a text mining approach for extracting sequence variants in biomedical literature
Miao Li, Dongqing Zhang, Zhihao Yang, Weiwei Li, Xiaobo Liu, and Jian Wang · 2013
Earlier work this paper cites.
Adult Cancer Clinical Trials That Fail to Complete: An Epidemic?
Kristian D. Stensland, Russell B. McBride, Asma Latif, Juan Wisnivesky, Ryan Hendricks, Nitin Roper, Paolo Boffetta, Simon J. Hall, William K. Oh, and Matthew D. Galsky · 2014
Earlier work this paper cites.
Gnormplus: An integrative approach for tagging genes, gene families, and protein domains
Chih-Hsuan Wei, Chun-Nan Hsu, Wen-Lian Hsu, Yung-Chuan Liu, and Hong-Jie Dai · 2015
Earlier work this paper cites.
EliIE: An open-source information extraction system for clinical trial eligibility criteria
Tian Kang, Shaodian Zhang, Youlan Tang, Gregory W Hruby, Alexander Rusanov, Noémie Elhadad, and Chunhua Weng · 2017
Earlier work this paper cites.
Learning eligibility in cancer clinical trials using deep neural networks
Aurelia Bustos and Antonio Pertusa · 2018
Earlier work this paper cites.
Systematic review and meta-analysis of the magnitude of structural, clinical, and physician and patient barriers to cancer clinical trial participation
Joseph M Unger, Riha Vaidya, Dawn L Hershman, Lori M Minasian, and Mark E Fleury · 2019
Earlier work this paper cites.
Criteria2query: a natural language interface to clinical databases for cohort definition
Chi Yuan, Patrick B Ryan, Casey Ta, Yixuan Guo, Ziran Li, Jill Hardin, Rupa Makadia, Peng Jin, Ning Shang, Tian Kang, and Chunhua Weng · 2019
Earlier work this paper cites.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei · 2020
Cited alongside, same era.
Compose: Cross-modal pseudo-siamese network for patient trial matching
Junyi Gao, Cao Xiao, Lucas M. Glass, and Jimeng Sun · 2020
Cited alongside, same era.
scispacy: Fast and robust models for biomedical natural language processing
Mark Neumann, Daniel King, Iz Beltagy, and Waleed Ammar · 2020
Cited alongside, same era.
Trialstreamer: Mapping and browsing medical evidence in real-time
Benjamin E. Nye, Ani Nenkova, Iain J. Marshall, and Byron C. Wallace · 2020
Cited alongside, same era.
Deepenroll: Patient-trial matching with deep embedding and entailment prediction
Xingyao Zhang, Cao Xiao, Lucas M. Glass, and Jimeng Sun · 2020
Cited alongside, same era.
Cancer statistics, 2022
Rebecca L. Siegel and Ahmedin Jemal · 2022
Later among the works it cites.
Sparks of artificial general intelligence: Early experiments with GPT-4, 2023
Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, Johannes Gehrke, Eric Horvitz, Ece Kamar, Peter Lee, Yin Tat Lee, Yuanzhi Li, Scott Lundberg, Harsha Nori, Hamid Palangi, Marco Tulio Ribeiro, and Yi Zhang · 2023
Closest in time.
Capabilities of GPT-4 on medical challenge problems, 2023
Harsha Nori, Nicholas King, Scott Mayer McKinney, Dean Carignan, and Eric Horvitz · 2023
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GPT-4 technical report, 2023
OpenAI · 2023
Closest in time.
Toward structuring real-world data: Deep learning for extracting oncology information from clinical text with patient-level supervision
Sam Preston, Mu Wei, Rajesh Rao, Robert Tinn, Naoto Usuyama, Michael Lucas, Yu Gu, Roshanthi Weerasinghe, Soohee Lee, Brian Piening, Paul Tittel, Naveen Valluri, Tristan Naumann, Carlo Bifulco, and Hoifung Poon · 2023
Closest in time.
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Oncotree: A cancer classification system for precision oncology
Ritika Kundra, Hongxin Zhang, Robert Sheridan, Sahussapont Joseph Sirintrapun, Avery Wang, Angelica Ochoa, Manda Wilson, Benjamin Gross, Yichao Sun, Ramyasree Madupuri, Baby A. Satravada, Dalicia Reales, Efsevia Vakiani, Hikmat A. Al-Ahmadie, Ahmet Dogan, Maria Arcila, Ahmet Zehir, Steven Maron, Michael F. Berger, Cristina Viaplana, Katherine Janeway, Matthew Ducar, Lynette Sholl, Snjezana Dogan, Philippe Bedard, Lea F. Surrey, Iker Huerga Sanchez, Aijaz Syed, Anoop Balakrishnan Rema, Debyani Chakravarty, Sarah Suehnholz, Moriah Nissan, Gopakumar V. Iyer, Rajmohan Murali, Nancy Bouvier, Robert A. Soslow, David Hyman, Anas Younes, Andrew Intlekofer, James J. Harding, Richard D. Carvajal, Paul J. Sabbatini, Ghassan K. Abou-Alfa, Luc Morris, Yelena Y. Janjigian, Meighan M. Gallagher, Tara A. Soumerai, Ingo K. Mellinghoff, Abraham A. Hakimi, Matthew Fury, Jason T. Huse, Aditya Bagrodia, Meera Hameed, Stacy Thomas, Stuart Gardos, Ethan Cerami, Tali Mazor, Priti Kumari, Pichai Raman, Priyanka Shivdasani, Suzanne MacFarland, Scott Newman, Angela Waanders, Jianjiong Gao, David Solit, and Nikolaus Schultz · 2021
Cited alongside, same era.
Training language models to follow instructions with human feedback, 2022
Long Ouyang, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll L. Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul Christiano, Jan Leike, and Ryan Lowe · 2022
Cited alongside, same era.
Benefits, limits, and risks of GPT-4 as an ai chatbot for medicine
Peter Lee, Sebastien Bubeck, and Joseph Petro
Cited in the paper.
The AI Revolution in Medicine: GPT-4 and Beyond
Peter Lee, Carey Goldberg, and Isaac Kohane
Cited in the paper.
U.S. National Library of Medicine · 2023
Closest in time.
Llm for patient-trial matching: Privacy-aware data augmentation towards better performance and generalizability, 2023
Jiayi Yuan, Ruixiang Tang, Xiaoqian Jiang, and Xia Hu · 2023
Closest in time.