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Department of Biostatistics
mathematical curves

Theory and Methods Development

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Theory and Methods Development

The emergence of statistical learning and deep learning in particular has led to increased interest in medical imaging analysis.

Medical Imaging Analysis

Medical images are a rich high-dimensional data source that can be used to help with tasks such as disease detection, monitoring, and characterization. The emergence of statistical learning and deep learning in particular has led to increased interest in medical imaging analysis. Several faculty members work on medical imaging analysis. For example, Dr. Lorin Crawford works on developing methods for identifying the physical features of 3D shapes that best explain variation between groups. Dr. Eloyan develops machine learning methods for tumor heterogeneity estimation, methods for brain functional connectivity, and biomarker estimation approaches for images collected from people with Alzheimer’s disease. Drs. Eloyan, Gatsonis, Duan, and Steingrimsson all work on investigating the statistical aspects of deep learning as well as methods for estimation and implementation of radiomics in imaging. 

  • Lorin Crawford

    Distinguished Senior Fellow in Biostatistics
    lorin_crawford@brown.edu
  • Ani Eloyan

    Vice Chair of the Department of Biostatistics, Associate Professor of Biostatistics
    ani_eloyan@brown.edu
  • Constantine Gatsonis

    Henry Ledyard Goddard Professor of Biostatistics, Director of the Center for Biostatistics and Health Data Science
    constantine_gatsonis@brown.edu
  • Fenghai Duan

    Professor of Biostatistics
    fenghai_duan@brown.edu
  • Jon Steingrimsson

    Associate Professor of Biostatistics, Director of the NextGen Graduate Program in Biostatistics
    jon_steingrimsson@brown.edu
Brown University School of Public Health
Providence RI 02903 401-863-3375 public_health@brown.edu

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Theory and Methods Development