Chunhua Weng, PhD, FACMI
Associate Professor of Biomedical Informatics
Columbia University, New York, NY
My long-term research interest is to accelerate clinical and translational science using electronic data while minimizing study design biases and optimizing study results’ generalizability. My approach combines formal methods and socio-technical approaches. I combine text knowledge engineering and health data analytics to improve the efficiency and generalizability of clinical research. My co-authors and I have created a distribution-based method for quantifying the collective generalizability of multiple clinical trials and a novel generalizability index for study traits (GIST), which have enabled scalable and proactive clinical study generalizability assessment. My team also explore the symbiosis between knowledge representation and natural language processing for text knowledge engineering, as reflected in our work on EliXR. I aim to advance the field of clinical research informatics on several fronts, including text knowledge engineering, aggregate analysis of clinical studies, quality-aware computational reuse of electronic patient data and public data, and clinical research workflow optimization in patient care settings towards the achievement of a learning health system. Currently I also spend a significant amount of my time leading the Columbia eMERGE project, as part of a national eMERGE network. I have published on the following topics:
Openings for research officer, postdoc, and research assistant are available immediately to model patient populations and quantify the population representativeness of clinical studies using electronic data sources. Highly motivated individuals with computing background and quantitative analytical skills are encouraged to apply. Prospective candidates can email a CV to me with “job application” in the subject line.
R, Weng C,
Case-based Reasoning Using Electronic Health Records
Patients for Clinical Trials, Journal of American
Association, 2015, in press.
Weng C#, Li Y#, Ryan P, Zhang Y, Gao J, Liu F, Bigger JT, Hripcsak G, A Distribution-based Method for Assessing The Differences between Clinical Trial Target Populations and Patient Populations in Electronic Health Records, Applied Clinical Informatics, Vol. 5: Issue 2 2014, 463-479. #: equal-contribution first authors.
* Miotto R, Jiang S, Weng C, eTACTS: A Method for Dynamically Filtering Clinical Trial Search Results, J Biomed Inform, 2013 Dec;46(6):1060-7. PMID: 23916863 (Open access PDF and eTACTS system)
* Weiskopf NG, Hripcsak G, Sushmita S, Weng C, Defining and measuring completeness for electronic health records for secondary use. J Biomed Inform, 2013 Oct;46(5):830-6. PMID: 23820016 (Best Talk for Day 2 of the 2013 NLM Informatics Training Conference) (Open access PDF)
* Weiskopf NG, Weng C, Methods and Dimensions of EHR Data Quality Assessment: Enabling Reuse for Clinical Research, J Am Med Inform Assoc. 2013 Jan 1;20(1):144-51, PMID: 22733976
Weng C, Li Y, Berhe S, Boland MR, Gao J, Hruby GW, Steinman RC, Lopez-Jimenez C, Busacca L, Hripcsak G, Bakken S, Bigger JT, An Integrated Model for Patient Care and Clinical Trials (IMPACT) to Support Clinical Research Visit Scheduling Workflow for Future Learning Health Systems, J Biomed Inform, 2013 May 16. PMID: 23684593.
Weng C, Appelbaum P, Hripcsak G, Kronish I, Busacca L, Davidson KW, Bigger JT, Using EHRs to Integrate Research with Patient Care: Promises and Challenges, J Am Med Inform Assoc, 2012, Sep 1;19(5):684-7, PMID: 22542813
Weng C, Wu X, Luo Z, Boland M, Theodoratos D, Johnson SB, EliXR: An Approach to Eligibility Criteria Extraction and Representation. J Am Med Inform Assoc, 2011: 18: i116-i124. PMID: 21807647 (Distinguished Paper of 2011 AMIA Clinical Research Informatics Summit).
Thadani S, Weng C*, Bigger JT, Ennever J, Wajngurt D, Electronic Screening Improves Efficiency of Clinical Trials Recruitment, J Am Med Inform Assoc, 2009, 16(6), 869-873. PMID: 19717797 (*: corresponding author)
Weng C, Gallagher D., Bales M., Bakken S., and Ginsberg H.N. Understanding Interdisciplinary Health Sciences Collaborations: A Campus-Wide Survey of Obesity Experts. Proc of 2008 AMIA Fall Symposium. 2008. 798-802. PMID: 18999235
Acknowledgment: Dr. Weng thanks the National Library of Medicine, the Department of Biomedical Informatics (DBMI), The Irving Institute for Clinical and Translational Research (CTSA), and Professional Schools Fund of Columbia University for funding her research.
Chunhua Weng, Ph.D., FACMI
Associate Professor of Biomedical Informatics
622 West 168 Street, PH-20-room 407
New York, NY 10032
University email account (@columbia.edu): chunhua
Google email: cweng2009 (Note: if you do not receive my reply from my university email, there is chance that I missed your emails; please feel free to use this alternative account. thank you!)
Last Updated: 01-2016