Linying Zhang

According to our database, Linying Zhang authored at least 22 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Semi-Supervised Transfer Learning Framework for Aging-Aware Library Characterization.

Zhengguang Tang, Cong Li, Hailong You, Zhixiong Di, Linying Zhang, Xingming Liu, Yu Wang, Yong Dai, Geng Bai

IEEE Trans. Circuits Syst. II Express Briefs, March, 2024

Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium.

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 Gursoy, Marzyeh Ghassemi, Emma Pierson, George H. Chen, Sanjat Kanjilal, Michael Oberst, Linying Zhang, Harvineet Singh, Tom Hartvigsen, Helen Zhou, Chinasa T. Okolo

CoRR, 2024

CEHR-GPT: Generating Electronic Health Records with Chronological Patient Timelines.

Chao Pang, Xinzhuo Jiang, Nishanth Parameshwar Pavinkurve, Krishna S. Kalluri, Elise L. Minto, Jason Patterson, Linying Zhang, George Hripcsak, Noémie Elhadad, Karthik Natarajan

CoRR, 2024

2023

Reproducible variability: assessing investigator discordance across 9 research teams attempting to reproduce the same observational study.

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

J. Am. Medical Informatics Assoc., April, 2023

2022

Adjusting for indirectly measured confounding using large-scale propensity score.

Linying Zhang, Yixin Wang, Martijn J. Schuemie, David M. Blei, George Hripcsak

J. Biomed. Informatics, 2022

Predicting hospitalization of COVID-19 positive patients using clinician-guided machine learning methods.

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

J. Am. Medical Informatics Assoc., 2022

A Bayesian Causal Inference Approach for Assessing Fairness in Clinical Decision-Making.

Linying Zhang, Lauren R. Richter, Yixin Wang, Anna Ostropolets, Noemie Elhadad, David M. Blei, George Hripcsak

CoRR, 2022

Using EHR Data and Machine Learning Methods to Predict Fall Injury.

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

Proceedings of the AMIA 2022, 2022

Using Data Assimilation to Predict Post-Operative Bariatric Surgery Glycemic Status in Adolescents.

Lauren R. Richter, Benjamin Albert, Linying Zhang, Ilene Fennoy, David J. Albers, George Hripcsak

Proceedings of the AMIA 2022, 2022

2021

Predicting pressure injury using nursing assessment phenotypes and machine learning methods.

Wenyu Song, Min-Jeoung Kang, Linying Zhang, Wonkyung Jung, Jiyoun Song, David W. Bates, Patricia C. Dykes

J. Am. Medical Informatics Assoc., 2021

Predicting Hospitalization of COVID-19 Positive Patients Using Machine Learning Methods.

Wenyu Song, Linying Zhang, Michael Sainlaire, Mehran Karvar, Min-Jeoung Kang, Avery Pullman, Anthony F. Massaro, Namrata Patil, Ravi Jasuja, Patricia C. Dykes

Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021

2020

A scoping review of clinical decision support tools that generate new knowledge to support decision making in real time.

Anna Ostropolets, Linying Zhang, George Hripcsak

J. Am. Medical Informatics Assoc., 2020

The Multi-Outcome Medical Deconfounder: Assessing Treatment Effect on Multiple Renal Measures.

Linying Zhang, Yixin Wang, Anna Ostropolets, Ruijun Chen, David M. Blei, George Hripcsak

Proceedings of the AMIA 2020, 2020

Predicting Pressure Injury Using Nursing Assessment Phenotype and Machine Learning Methods.

Wenyu Song, Min-Jeoung Kang, Linying Zhang, Jose P. Garcia, David W. Bates, Patricia C. Dykes

Proceedings of the AMIA 2020, 2020

Causal Inference from Observational Healthcare Data: Implications, Impacts and Innovations.

George Hripcsak, David M. Blei, Elias Bareinboim, Martijn J. Schuemie, Linying Zhang

Proceedings of the AMIA 2020, 2020

Evaluation of Large-scale Propensity Score Modeling and Covariate Balance on Potential Unmeasured Confounding in Observational Research.

Ruijun Chen, Martijn J. Schuemie, Marc A. Suchard, Anna Ostropolets, Linying Zhang, Patrick B. Ryan, George Hripcsak

Proceedings of the AMIA 2020, 2020

2019

The Medical Deconfounder: Assessing Treatment Effect with Electronic Health Records (EHRs).

Linying Zhang, Yixin Wang, Anna Ostropolets, Jami J. Mulgrave, David M. Blei, George Hripcsak

CoRR, 2019

The Medical Deconfounder: Assessing Treatment Effects with Electronic Health Records.

Linying Zhang, Yixin Wang, Anna Ostropolets, Jami J. Mulgrave, David M. Blei, George Hripcsak

Proceedings of the Machine Learning for Healthcare Conference, 2019

Personalized treatment for type 2 diabetes using weighted k-nearest neighbors.

Wenyu Song, Linying Zhang, Emily Gill, Jeremiah Zhe Liu, Adam Wright

Proceedings of the AMIA 2019, 2019

Investigating female-male differences in risk factors for myocardial infarction using OHDSI tools.

Anna Ostropolets, Linying Zhang, Jami Jackson Mulgrave, George Hripcsak

Proceedings of the AMIA 2019, 2019

2018

Evaluating Reinforcement Learning Algorithms in Observational Health Settings.

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

CoRR, 2018

2016

A novel flexible activity refinement approach for improving workflow process flexibility.

Yanrong Jiang, Nanfeng Xiao, Yufeng Zhang, Linying Zhang

Comput. Ind., 2016