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
Time-dependent Predictive Values of Prognostic Biomarkers with Failure Time Outcome.
Reduced-dose CT: effect on reader evaluation in detection of pulmonary embolism.
Authors: MacKenzie JD, Nazario-Larrieu J, Cai T, Ledbetter MS, Duran-Mendicuti MA, Judy PF, Rybicki FJ.
AJR Am J Roentgenol
View full abstract on Pubmed
AJR Am J Roentgenol
View full abstract on Pubmed
Time-resolved MR angiography: a primary screening examination of patients with suspected pulmonary embolism and contraindications to administration of iodinated contrast material.
Authors: Ersoy H, Goldhaber SZ, Cai T, Luu T, Rosebrook J, Mulkern R, Rybicki F.
AJR Am J Roentgenol
View full abstract on Pubmed
AJR Am J Roentgenol
View full abstract on Pubmed
Model checking for ROC regression analysis.
Predicting clustered dental implant survival using frailty methods.
The sensitivity and specificity of markers for event times.
Application of the time-dependent ROC curves for prognostic accuracy with multiple biomarkers.
Combining predictors for classification using the area under the receiver operating characteristic curve.
Joint inferences on vaccine efficacy against infection and disease with application to the first HIV vaccine efficacy trial.
Frailty approach for the analysis of clustered failure time observations in dental research.
