Tianxi Cai, ScD
Professor of Biomedical Informatics, Harvard Medical School
John Rock Professor of Population and Translational Data Sciences, Harvard T.H. Chan School of Public Health
Director, Translational Data Science Center for a Learning Health System (CELEHS)
Tianxi Cai is a major player in developing analytical tools for mining EHR data and predictive modeling with biomedical data. She provides statistical leadership on several large-scale projects, including the NIH-funded Undiagnosed Diseases Network at DBMI. Cai's research lab develops novel statistical and machine learning methods for several areas including clinical trials, real world evidence, and personalized medicine using genomic and phenomic data. Cai received her ScD in Biostatistics at Harvard and was an assistant professor at the University of Washington before returning to Harvard as a faculty member in 2002.
DBMI Research Areas
Large-scale identification of patients with cerebral aneurysms using natural language processing.
Authors: Castro VM, Dligach D, Finan S, Yu S, Can A, Abd-El-Barr M, Gainer V, Shadick NA, Murphy S, Cai T, Savova G, Weiss ST, Du R.
Neurology
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Neurology
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Robust Dynamic Risk Prediction with Longitudinal Studies.
Limited Hospital Variation in the Use and Yield of CT for Pulmonary Embolism in Patients Undergoing Total Hip or Total Knee Replacement Surgery.
Authors: Kumamaru KK, Kumamaru H, Bateman BT, Gronsbell J, Cai T, Liu J, Higgins LD, Aoki S, Ohtomo K, Rybicki FJ, Patorno E.
Radiology
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Radiology
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Optimal stratification in outcome prediction using baseline information.
Estimation and testing for multiple regulation of multivariate mixed outcomes.
Prioritizing individual genetic variants after kernel machine testing using variable selection.
Authors: He Q, Cai T, Liu Y, Zhao N, Harmon QE, Almli LM, Binder EB, Engel SM, Ressler KJ, Conneely KN, Lin X, Wu MC.
Genet Epidemiol
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Genet Epidemiol
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Robust risk prediction with biomarkers under two-phase stratified cohort design.
Identifying predictive markers for personalized treatment selection.
Inference for survival prediction under the regularized Cox model.
A predictive enrichment procedure to identify potential responders to a new therapy for randomized, comparative controlled clinical studies.
Authors: Li J, Zhao L, Tian L, Cai T, Claggett B, Callegaro A, Dizier B, Spiessens B, Ulloa-Montoya F, Wei LJ.
Biometrics
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Biometrics
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