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Clinical trials are indispensable for medical research and the development of new treatments.
The cost of privacy: destruction of data-mining utility in anonymized data publishing
Justin Brickell and Vitaly Shmatikov · 2008
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Privacy-preserving data publishing: A survey of recent developments
Benjamin CM Fung, Ke Wang, Rui Chen, and Philip S Yu · 2010
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Mining electronic health records: towards better research applications and clinical care
Peter B Jensen, Lars J Jensen, and Søren Brunak · 2012
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Toward practicing privacy
Cynthia Dwork and Rebecca Pottenger · 2013
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Doctor ai: Predicting clinical events via recurrent neural networks
Edward Choi, Mohammad Taha Bahadori, Andy Schuetz, Walter F Stewart, and Jimeng Sun · 2016
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Wasserstein generative adversarial networks
Martin Arjovsky, Soumith Chintala, and Léon Bottou · 2017
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Boosting deep learning risk prediction with generative adversarial networks for electronic health records
Zhengping Che, Yu Cheng, Shuangfei Zhai, Zhaonan Sun, and Yan Liu · 2017
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Generating multi-label discrete patient records using generative adversarial networks
Edward Choi, Siddharth Biswal, Bradley Malin, Jon Duke, Walter F Stewart, and Jimeng Sun · 2017
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Using recurrent neural network models for early detection of heart failure onset
Edward Choi, Andy Schuetz, Walter F Stewart, and Jimeng Sun · 2017
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Real-valued (medical) time series generation with recurrent conditional gans
Cristóbal Esteban, Stephanie L Hyland, and Gunnar Rätsch · 2017
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Improved training of wasserstein gans
Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, and Aaron C Courville · 2017
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Learning representations for the early detection of sepsis with deep neural networks
Hye Jin Kam and Ha Young Kim · 2017
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Estimating individual treatment effect: generalization bounds and algorithms
Uri Shalit, Fredrik D Johansson, and David Sontag · 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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Alexandre Yahi, Rami Vanguri, Noémie Elhadad, and Nicholas P Tatonetti · 2017
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Opportunities and obstacles for deep learning in biology and medicine
Travers Ching, Daniel S Himmelstein, Brett K Beaulieu-Jones, Alexandr A Kalinin, Brian T Do, Gregory P Way, Enrico Ferrero, Paul-Michael Agapow, Michael Zietz, Michael M Hoffman, et al · 2018
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Scalable and accurate deep learning with electronic health records
Alvin Rajkomar, Eyal Oren, Kai Chen, Andrew M Dai, Nissan Hajaj, Michaela Hardt, Peter J Liu, Xiaobing Liu, Jake Marcus, Mimi Sun, et al · 2018
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Synthesizing electronic health records using improved generative adversarial networks
Mrinal Kanti Baowaly, Chia-Ching Lin, Chao-Lin Liu, and Kuan-Ta Chen · 2019
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Machine learning of physiological waveforms and electronic health record data to predict, diagnose and treat haemodynamic instability in surgical patients: protocol for a retrospective study
Maxime Cannesson, Ira Hofer, Joseph Rinehart, Christine Lee, Kathirvel Subramaniam, Pierre Baldi, Artur Dubrawski, and Michael R Pinsky · 2019
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A machine-learning-based prediction method for hypertension outcomes based on medical data
Wenbing Chang, Yinglai Liu, Yiyong Xiao, Xinglong Yuan, Xingxing Xu, Siyue Zhang, and Shenghan Zhou · 2019
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Comparison of artificial neural network and logistic regression models for prediction of outcomes in trauma patients: A systematic review and meta-analysis
Soheil Hassanipour, Haleh Ghaem, Morteza Arab-Zozani, Mozhgan Seif, Mohammad Fararouei, Elham Abdzadeh, Golnar Sabetian, and Shahram Paydar · 2019
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A novel cloud-based framework for the elderly healthcare services using digital twin
Ying Liu, Lin Zhang, Yuan Yang, Longfei Zhou, Lei Ren, Fei Wang, Rong Liu, Zhibo Pang, and M Jamal Deen · 2019
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Integrated identification of disease specific pathways using multi-omics data
Yingzhou Lu, Yi-Tan Chang, Eric P Hoffman, Guoqiang Yu, David M Herrington, Robert Clarke, Chiung-Ting Wu, Lulu Chen, and Yue Wang · 2019
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Deep recurrent survival analysis
Kan Ren, Jiarui Qin, Lei Zheng, Zhengyu Yang, Weinan Zhang, Lin Qiu, and Yong Yu · 2019
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Treatment effect prediction with adversarial deep learning using electronic health records
Jiebin Chu, Wei Dong, Jinliang Wang, Kunlun He, and Zhengxing Huang · 2020
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A digital twins machine learning model for forecasting disease progression in stroke patients
Angier Allen, Anna Siefkas, Emily Pellegrini, Hoyt Burdick, Gina Barnes, Jacob Calvert, Qingqing Mao, and Ritankar Das · 2021
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Eva: Generating longitudinal electronic health records using conditional variational autoencoders
Siddharth Biswal, Soumya Ghosh, Jon Duke, Bradley Malin, Walter Stewart, Cao Xiao, and Jimeng Sun · 2021
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Electrocardio panorama: synthesizing new ECG views with self-supervision
Jintai Chen, Xiangshang Zheng, Hongyun Yu, Danny Z Chen, and Jian Wu · 2021
Cited alongside, same era.
Mimosa: Multi-constraint molecule sampling for molecule optimization
Tianfan Fu, Cao Xiao, Xinhao Li, Lucas M Glass, and Jimeng Sun · 2021
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Generative adversarial networks (gans) challenges, solutions, and future directions
Divya Saxena and Jiannong Cao · 2021
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Feature extraction from unequal length heterogeneous ehr time series via dynamic time warping and tensor decomposition
Chi Zhang, Hadi Fanaee-T, and Magne Thoresen · 2021
Cited alongside, same era.
Synteg: a framework for temporal structured electronic health data simulation
Ziqi Zhang, Chao Yan, Thomas A Lasko, Jimeng Sun, and Bradley A Malin · 2021
Cited alongside, same era.
Embracing large language models for medical applications: opportunities and challenges
Mert Karabacak and Konstantinos Margetis · 2023
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Machine learning for synthetic data generation: a review
Yingzhou Lu, Minjie Shen, Huazheng Wang, Xiao Wang, Capucine van Rechem, and Wenqi Wei · 2023
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Capabilities of gpt-4 on medical challenge problems
Harsha Nori, Nicholas King, Scott Mayer McKinney, Dean Carignan, and Eric Horvitz · 2023
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Llm-driven multimodal target volume contouring in radiation oncology
Yujin Oh, Sangjoon Park, Hwa Kyung Byun, Jin Sung Kim, and Jong Chul Ye · 2023
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Synthetic clinical trial data while preserving subject-level privacy
Mandis Beigi, Afrah Shafquat, Jason Mezey, and Jacob W Aptekar · 2022
Cited alongside, same era.
ME-GAN: Learning panoptic electrocardio representations for multi-view ECG synthesis conditioned on heart diseases
Jintai Chen, Kuanlun Liao, Kun Wei, Haochao Ying, Danny Z Chen, and Jian Wu · 2022
Cited alongside, same era.
The health digital twin to tackle cardiovascular disease—a review of an emerging interdisciplinary field
Genevieve Coorey, Gemma A Figtree, David F Fletcher, Victoria J Snelson, Stephen Thomas Vernon, David Winlaw, Stuart M Grieve, Alistair McEwan, Jean Yee Hwa Yang, Pierre Qian, et al · 2022
Cited alongside, same era.
Differentiable scaffolding tree for molecular optimization
Tianfan Fu, Wenhao Gao, Cao Xiao, Jacob Yasonik, Connor W Coley, and Jimeng Sun · 2022
Cited alongside, same era.
Hint: Hierarchical interaction network for clinical-trial-outcome predictions
Tianfan Fu, Kexin Huang, Cao Xiao, Lucas M Glass, and Jimeng Sun · 2022
Cited alongside, same era.
Obesity prediction with ehr data: A deep learning approach with interpretable elements
Mehak Gupta, Thao-Ly T Phan, H Timothy Bunnell, and Rahmatollah Beheshti · 2022
Cited alongside, same era.
Digital twins and hybrid modelling for simulation of physiological variables and stroke risk
Tilda Herrgårdh, Elizabeth Hunter, Kajsa Tunedal, Håkan Örman, Julia Amann, Francisco Abad Navarro, Catalina Martinez-Costa, John D Kelleher, and Gunnar Cedersund · 2022
Cited alongside, same era.
Minjie Shen, Yue Zhao, Chenhao Li, Fan Meng, Xiao Wang, David Herrington, Yue Wang, Tim Fu, and Capucine Van Rechem · 2023
Later among the works it cites.
Large language models in medicine
Arun James Thirunavukarasu, Darren Shu Jeng Ting, Kabilan Elangovan, Laura Gutierrez, Ting Fang Tan, and Daniel Shu Wei Ting · 2023
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Digital twin for healthcare systems
Alexandre Vallée · 2023
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Large language model (llm)-driven chatbots for neuro-ophthalmic medical education
Ethan Waisberg, Joshua Ong, Mouayad Masalkhi, and Andrew G Lee · 2023
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Augmenting black-box llms with medical textbooks for clinical question answering
Yubo Wang, Xueguang Ma, and Wenhu Chen · 2023
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A medical diagnostic assistant based on llm
Chengyan Wu, Zehong Lin, Wenlong Fang, and Yuyan Huang · 2023
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Text2Tree: Aligning text representation to the label tree hierarchy for imbalanced medical classification
Jiahuan Yan, Haojun Gao, Zhang Kai, Weize Liu, Danny Chen, Jian Wu, and Jintai Chen · 2023
Later among the works it cites.
Ehr-safe: generating high-fidelity and privacy-preserving synthetic electronic health records
Jinsung Yoon, Michel Mizrahi, Nahid Farhady Ghalaty, Thomas Jarvinen, Ashwin S Ravi, Peter Brune, Fanyu Kong, Dave Anderson, George Lee, Arie Meir, et al · 2023
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Uncertainty quantification on clinical trial outcome prediction
Tianyi Chen, Nan Hao, Yingzhou Lu, and Capucine Van Rechem · 2024
Closest in time.
Medalign: A clinician-generated dataset for instruction following with electronic medical records
Scott L Fleming, Alejandro Lozano, William J Haberkorn, Jenelle A Jindal, Eduardo Reis, Rahul Thapa, Louis Blankemeier, Julian Z Genkins, Ethan Steinberg, Ashwin Nayak, et al · 2024
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Healai: A healthcare llm for effective medical documentation
Sagar Goyal, Eti Rastogi, Sree Prasanna Rajagopal, Dong Yuan, Fen Zhao, Jai Chintagunta, Gautam Naik, and Jeff Ward · 2024
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Few shot chain-of-thought driven reasoning to prompt llms for open ended medical question answering
Ojas Gramopadhye, Saeel Sandeep Nachane, Prateek Chanda, Ganesh Ramakrishnan, Kshitij Sharad Jadhav, Yatin Nandwani, Dinesh Raghu, and Sachindra Joshi · 2024
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Uncertainty quantification and interpretability for clinical trial approval prediction
Yingzhou Lu, Tianyi Chen, Nan Hao, Capucine Van Rechem, Jintai Chen, and Tianfan Fu · 2024
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Model tuning or prompt tuning? a study of large language models for clinical concept and relation extraction
Cheng Peng, Xi Yang, Kaleb E Smith, Zehao Yu, Aokun Chen, Jiang Bian, and Yonghui Wu · 2024
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Wenqi Shi, Ran Xu, Yuchen Zhuang, Yue Yu, Jieyu Zhang, Hang Wu, Yuanda Zhu, Joyce Ho, Carl Yang, and May D Wang · 2024
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Ting Fang Tan, Kabilan Elangovan, Liyuan Jin, Yao Jie, Li Yong, Joshua Lim, Stanley Poh, Wei Yan Ng, Daniel Lim, Yuhe Ke, et al · 2024
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Junda Wang, Zhichao Yang, Zonghai Yao, and Hong Yu · 2024
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Igamt: Privacy-preserving electronic health record synthesization with heterogeneity and irregularity
Wenjie Wang, Pengfei Tang, Jian Lou, Yuanming Shao, Lance Waller, Yi-an Ko, and Li Xiong · 2024
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Jiahuan Yan, Jintai Chen, Chaowen Hu, Bo Zheng, Yaojun Hu, Jimeng Sun, and Jian Wu · 2024
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Making pre-trained language models great on tabular prediction
Jiahuan Yan, Bo Zheng, Hongxia Xu, Yiheng Zhu, Danny Chen, Jimeng Sun, Jian Wu, and Jintai Chen · 2024
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Designing clinical trials for patients who are not average
Thomas E Yankeelov, David A Hormuth, Ernesto ABF Lima, Guillermo Lorenzo, Chengyue Wu, Lois C Okereke, Gaiane M Rauch, Aradhana M Venkatesan, and Caroline Chung · 2024
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A continued pretrained llm approach for automatic medical note generation
Dong Yuan, Eti Rastogi, Gautam Naik, Jai Chintagunta, Sree Prasanna Rajagopal, Fen Zhao, Sagar Goyal, and Jeff Ward · 2024
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