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Tianxi Cai, Sc.D.

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Biography
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Harvard UniversitySc.D.1999

Overview
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Dr. Cai’s current research interests are mainly in the area of biomarker evaluation; model selection and validation; prediction methods; personalized medicine in disease diagnosis, prognosis and treatment; statistical inference with high dimensional data; and survival analysis.

In addition to her methdological research, Dr. Cai also collaborates with the I2B2 (Informatics for Integrating Biology and the Bedside) center on developing a scalable informatics framework that will bridge clinical research data and the vast data banks arising from basic science research in order to better understand the genetic bases of complex diseases.

Research
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The research activities and funding listed below are automatically derived from NIH ExPORTER and other sources, which might result in incorrect or missing items. Faculty can login to make corrections and additions.
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  1. U01FD007929 (BOURGEOIS, FLORENCE) Sep 1, 2023 - Aug 31, 2026
    NIH
    Generating Reproducible Real-World Evidence with Multi-Source Data to Capture Unstructured Clinical Endpoints for Chronic Diseases
    Role: Co-Principal Investigator
  2. R01AR080193 (LIAO, KATHERINE PHOENIX) Jul 1, 2022 - Jun 30, 2026
    NIH
    Bridging clinical trial and real-world data via machine learning to advance rheumatoid arthritis treatment strategies
    Role: Co-Principal Investigator
  3. R01LM013614 (CAI, TIANXI) Aug 1, 2021 - Apr 30, 2025
    NIH
    Semi-supervised Approaches to Denoising Electronic Health Records Data for Risk Prediction
    Role: Principal Investigator
  4. R21AR078339 (CAI, TIANXI ;LIAO, KATHERINE PHOENIX) Jul 1, 2021 - Jun 30, 2023
    NIH
    Studying exceptional treatment non-responders and genetics to predict treatment response in rheumatoid arthritis
    Role: Co-Principal Investigator
  5. R21CA242940 (CAI, TIANXI) Jul 1, 2019 - Jun 30, 2021
    NIH
    Semi-supervised Algorithms for Risk Assessment with Noisy EHR Data
    Role: Principal Investigator

Bibliographic
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© 2024 President and Fellows of Harvard College
Funded by the NIH National Center for Advancing Translational Sciences through its Clinical and Translational Science Awards Program, grant number UL1TR002541.