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2020 – today
- 2024
[j8]Linying Zhang
, Lauren R. Richter, Yixin Wang, Anna Ostropolets, Noémie Elhadad, David M. Blei, George Hripcsak:
Causal fairness assessment of treatment allocation with electronic health records. J. Biomed. Informatics 155: 104656 (2024)- [j7]Zhengguang Tang, Cong Li, Hailong You, Zhixiong Di, Linying Zhang, Xingming Liu, Yu Wang, Yong Dai, Geng Bai:
Semi-Supervised Transfer Learning Framework for Aging-Aware Library Characterization. IEEE Trans. Circuits Syst. II Express Briefs 71(3): 1156-1160 (2024) - [i6]Chao Pang, Xinzhuo Jiang, Nishanth Parameshwar Pavinkurve, Krishna S. Kalluri, Elise L. Minto, Jason Patterson, Linying Zhang, George Hripcsak, Noémie Elhadad, Karthik Natarajan:
CEHR-GPT: Generating Electronic Health Records with Chronological Patient Timelines. CoRR abs/2402.04400 (2024) - [i5]Hyewon Jeong, Sarah Jabbour, Yuzhe Yang, Rahul Thapa, Hussein Mozannar, William Jongwon Han, Nikita Mehandru, Michael Wornow, Vladislav Lialin, Xin Liu, Alejandro Lozano, Jiacheng Zhu, Rafal Dariusz Kocielnik, Keith Harrigian, Haoran Zhang, Edward Lee, Milos Vukadinovic, Aparna Balagopalan, Vincent Jeanselme, Katherine Matton, Ilker Demirel, Jason A. Fries, Parisa Rashidi, Brett K. Beaulieu-Jones, Xuhai Orson Xu, Matthew B. A. McDermott, Tristan Naumann, Monica Agrawal, Marinka Zitnik, Berk Ustun, Edward Choi, Kristen Yeom, Gamze Gürsoy, Marzyeh Ghassemi, Emma Pierson, George H. Chen, Sanjat Kanjilal, Michael Oberst, Linying Zhang, Harvineet Singh, Tom Hartvigsen, Helen Zhou, Chinasa T. Okolo:
Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium. CoRR abs/2403.01628 (2024) - [i4]Linying Zhang, Stefano Pagani, Jun Zhang, Francesco Regazzoni:
Shape-informed surrogate models based on signed distance function domain encoding. CoRR abs/2409.12400 (2024) - 2023
- [j6]Anna Ostropolets, Yasser Albogami, Mitchell Conover, Juan M. Banda, William A. Baumgartner Jr., Clair Blacketer, Priyamvada Desai, Scott L. DuVall, Stephen P. Fortin, James P. Gilbert, Asieh Golozar, Joshua Ide, Andrew S. Kanter, David M. Kern, Chungsoo Kim, Lana Y. H. Lai, Chenyu Li, Feifan Liu, Kristine E. Lynch, Evan Minty, Maria Inês Neves, Ding Quan Ng, Tontel Obene, Victor Pera, Nicole Pratt, Gowtham Rao, Nadav Rappoport, Ines Reinecke, Paola Saroufim, Azza Shoaibi, Katherine Simon, Marc A. Suchard, Joel N. Swerdel, Erica A. Voss, James Weaver, Linying Zhang, George Hripcsak, Patrick B. Ryan:
Reproducible variability: assessing investigator discordance across 9 research teams attempting to reproduce the same observational study. J. Am. Medical Informatics Assoc. 30(5): 859-868 (2023) - [c12]Linying Zhang, Xiao Yang, Qiuxian Chen:
Multi-Round Reasoning Incorporating Prior Knowledge in Conversational Sentiment Analysis. AIPR 2023: 1212-1218 - [c11]Qiuxian Chen, Linying Zhang:
GLKE: Global-Local Knowledge Enhanced Text Matching Model. AIPR 2023: 1249-1254 - 2022
- [j5]Wenyu Song, Linying Zhang, Luwei Liu, Michael Sainlaire, Mehran Karvar, Min-Jeoung Kang, Avery Pullman, Stuart R. Lipsitz, Anthony F. Massaro, Namrata Patil, Ravi Jasuja, Patricia C. Dykes:
Predicting hospitalization of COVID-19 positive patients using clinician-guided machine learning methods. J. Am. Medical Informatics Assoc. 29(10): 1661-1667 (2022) - [j4]Linying Zhang, Yixin Wang, Martijn J. Schuemie, David M. Blei, George Hripcsak:
Adjusting for indirectly measured confounding using large-scale propensity score. J. Biomed. Informatics 134: 104204 (2022) - [c10]Lauren R. Richter, Benjamin Albert, Linying Zhang, Ilene Fennoy, David J. Albers, George Hripcsak:
Using Data Assimilation to Predict Post-Operative Bariatric Surgery Glycemic Status in Adolescents. AMIA 2022 - [c9]Wenyu Song, Luwei Liu, Hannah Rice, Michael Sainlaire, Lillian Min, Linying Zhang, Tien Thai, Min-Jeoung Kang, Mica Curtin-Bowen, Stuart R. Lipsitz, Lipika Samal, Nancy Latham, Patricia C. Dykes:
Using EHR Data and Machine Learning Methods to Predict Fall Injury. AMIA 2022 - [i3]Linying Zhang, Lauren R. Richter, Yixin Wang, Anna Ostropolets, Noemie Elhadad, David M. Blei, George Hripcsak:
A Bayesian Causal Inference Approach for Assessing Fairness in Clinical Decision-Making. CoRR abs/2211.11183 (2022) - 2021
- [j3]Wenyu Song, Min-Jeoung Kang, Linying Zhang, Wonkyung Jung, Jiyoun Song, David W. Bates, Patricia C. Dykes:
Predicting pressure injury using nursing assessment phenotypes and machine learning methods. J. Am. Medical Informatics Assoc. 28(4): 759-765 (2021) - [c8]Wenyu Song, Linying Zhang, Michael Sainlaire, Mehran Karvar, Min-Jeoung Kang, Avery Pullman, Anthony F. Massaro, Namrata Patil, Ravi Jasuja, Patricia C. Dykes:
Predicting Hospitalization of COVID-19 Positive Patients Using Machine Learning Methods. AMIA 2021 - 2020
- [j2]Anna Ostropolets, Linying Zhang, George Hripcsak:
A scoping review of clinical decision support tools that generate new knowledge to support decision making in real time. J. Am. Medical Informatics Assoc. 27(12): 1968-1976 (2020) - [c7]Ruijun Chen, Martijn J. Schuemie, Marc A. Suchard, Anna Ostropolets, Linying Zhang, Patrick B. Ryan, George Hripcsak:
Evaluation of Large-scale Propensity Score Modeling and Covariate Balance on Potential Unmeasured Confounding in Observational Research. AMIA 2020 - [c6]George Hripcsak, David M. Blei, Elias Bareinboim, Martijn J. Schuemie, Linying Zhang:
Causal Inference from Observational Healthcare Data: Implications, Impacts and Innovations. AMIA 2020 - [c5]Wenyu Song, Min-Jeoung Kang, Linying Zhang, Jose P. Garcia, David W. Bates, Patricia C. Dykes:
Predicting Pressure Injury Using Nursing Assessment Phenotype and Machine Learning Methods. AMIA 2020 - [c4]Linying Zhang, Yixin Wang, Anna Ostropolets, Ruijun Chen, David M. Blei, George Hripcsak:
The Multi-Outcome Medical Deconfounder: Assessing Treatment Effect on Multiple Renal Measures. AMIA 2020
2010 – 2019
- 2019
- [c3]Anna Ostropolets, Linying Zhang, Jami Jackson Mulgrave, George Hripcsak:
Investigating female-male differences in risk factors for myocardial infarction using OHDSI tools. AMIA 2019 - [c2]Wenyu Song, Linying Zhang, Emily Gill, Jeremiah Zhe Liu, Adam Wright:
Personalized treatment for type 2 diabetes using weighted k-nearest neighbors. AMIA 2019 - [c1]Linying Zhang, Yixin Wang, Anna Ostropolets, Jami J. Mulgrave, David M. Blei, George Hripcsak:
The Medical Deconfounder: Assessing Treatment Effects with Electronic Health Records. MLHC 2019: 490-512 - [i2]Linying Zhang, Yixin Wang, Anna Ostropolets, Jami J. Mulgrave, David M. Blei, George Hripcsak:
The Medical Deconfounder: Assessing Treatment Effect with Electronic Health Records (EHRs). CoRR abs/1904.02098 (2019) - 2018
- [i1]Omer Gottesman, Fredrik D. Johansson, Joshua Meier, Jack Dent, Donghun Lee, Srivatsan Srinivasan, Linying Zhang, Yi Ding, David Wihl, Xuefeng Peng, Jiayu Yao, Isaac Lage, Christopher Mosch, Li-Wei H. Lehman, Matthieu Komorowski, Aldo Faisal, Leo Anthony Celi, David A. Sontag, Finale Doshi-Velez:
Evaluating Reinforcement Learning Algorithms in Observational Health Settings. CoRR abs/1805.12298 (2018) - 2016
- [j1]Yanrong Jiang, Nanfeng Xiao, Yufeng Zhang, Linying Zhang:
A novel flexible activity refinement approach for improving workflow process flexibility. Comput. Ind. 80: 1-15 (2016)
Coauthor Index
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