School of Medicine


Showing 1-5 of 5 Results

  • Andrei Iagaru

    Andrei Iagaru

    Professor of Radiology (Nuclear Medicine) at the Stanford University Medical Center

    Current Research and Scholarly InterestsCurrent research projects include:
    1) PET/MRI and PET/CT for Early Cancer Detection
    2) Targeted Radionuclide Therapy
    3) Clinical Translation of Novel PET Radiopharmaceuticals;

  • Juliana Idoyaga

    Juliana Idoyaga

    Assistant Professor of Microbiology and Immunology

    Current Research and Scholarly InterestsThe Idoyaga Lab is focused on the function and biology of dendritic cells, which are specialized antigen-presenting cells that initiate and modulate our body’s immune responses. Considering their importance in orchestrating the quality and quantity of immune responses, dendritic cells are an indisputable target for vaccines and therapies.

    Dendritic cells are not one cell type, but a network of cells comprised of many subsets or subpopulations with distinct developmental pathways and tissue localization. It is becoming apparent that each dendritic cell subset is different in its capacity to induce and modulate specific types of immune responses; however, there is still a lack of resolution and deep understanding of dendritic cell subset functional specialization. This gap in knowledge is an impediment for the rational design of immune interventions. Our research program focuses on advancing our understanding of mouse and human dendritic cell subsets, revealing their endowed capacity to induce distinct types of immune responses, and designing novel strategies to exploit them for vaccines and therapies.

  • Debra M. Ikeda, M.D.

    Debra M. Ikeda, M.D.

    Professor of Radiology (Breast Imaging)

    Current Research and Scholarly InterestsMy research interests are mammography positioning, tomosynthesis (DBT) cancer detection and diagnosis, MRI, DWI, MRI-guided breast biopsy, breast cancer recurrence, tattoo/ fiducial/wire localization of axillary lymph nodes, breast cancer and FDG PET-CT imaging, artifical intelligence/deep learning, breast density, density notification legislation, COVID-19 effects on Breast Imaging Centers and personnel

  • John P.A. Ioannidis

    John P.A. Ioannidis

    Professor of Medicine (Stanford Prevention Research), of Epidemiology and Population Health and by courtesy, of Statistics and of Biomedical Data Science

    Current Research and Scholarly InterestsMeta-research
    Evidence-based medicine
    Clinical and molecular epidemiology
    Human genome epidemiology
    Research design
    Reporting of research
    Empirical evaluation of bias in research
    Randomized trials
    Statistical methods and modeling
    Meta-analysis and large-scale evidence
    Prognosis, predictive, personalized, precision medicine and health
    Sociology of science

  • Haruka Itakura

    Haruka Itakura

    Assistant Professor of Medicine (Oncology) at the Stanford University Medical Center

    BioDr. Itakura is an Assistant Professor of Medicine (Oncology) in the Stanford University School of Medicine and practicing oncologist at the Stanford Cancer Center with background in biomedical informatics. She is a physician-scientist whose research mission is to drive medical advances at the intersection of cancer and data science research. Specifically, she aims to innovate state-of-the-art technologies to extract clinically useful knowledge from heterogeneous multi-scale biomedical data to improve diagnostics and therapeutics in cancer. She is a board-certified hematologist-oncologist and informaticist with specialized training in basic science, health services, and translational research. Her clinical background in oncology and PhD training in Biomedical Informatics position her to develop and apply data science methodologies on heterogeneous, multi-scale cancer data to extract actionable knowledge that can improve patient outcomes. Her ongoing research to develop and apply cutting-edge knowledge and skills to pioneer new robust methodologies for analyzing cancer big data is being supported by an NIH K01 Career Development Award in Biomedical Big Data Science. Her research focuses on developing and applying machine learning frameworks and radiogenomic approaches for the integrative analysis of heterogeneous, multi-scale data to accelerate discoveries in cancer diagnostics and therapeutics. Projects include prediction modeling of survival and treatment response, biomarker discovery, cancer subtype discovery, and identification of new therapeutic targets.