Chunhua Weng

Chunhua Weng Columbia University
Assistant Professor
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PhD

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Research Summary

My long-term research interest is to accelerate clinical and translational science using electronic data while minimizing study design biases and optimizing study resultsÕÇ 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:

Õ¥ clinical research generalizabilty understanding and improvement
Õ¥ assessment of EHR data quality to guide research use
Õ¥ informatics approaches to clinical trial E-screening and recruitment
Õ¥ use of EHRs for clinical research and development of a learning health system
Õ¥ systems and methods for evaluating the effectiveness of interdisciplinary team science
Õ¥ text knowledge engineering

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2012-2015

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