School of Medicine
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Clinical Assistant Professor, Medicine - Hematology
Bio Dr. Iberri is a medical oncologist and hematologist who specializes in the treatment of hematologic malignancies. His clinical practices runs the gamut of malignant and non-malignant hematologic disorders including acute and chronic leukemias, multiple myeloma and lymphomas, and bleeding and thrombotic disorders. He is actively involved in clinical trials evaluating novel agents in hematologic malignancies. His research interests are in the development and application of biomarkers to select patients most likely to benefit from therapy.
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 Interests Meta-research
Clinical and molecular epidemiology
Human genome epidemiology
Reporting of research
Empirical evaluation of bias in research
Statistical methods and modeling
Meta-analysis and large-scale evidence
Prognosis, predictive, personalized, precision medicine and health
Sociology of science
Clinical Associate Professor, Medicine - Primary Care and Population Health
Current Research and Scholarly Interests My research interests include the use and abuse of anabolic steroids and other performance enhancing/cognitive enhacing drugs.
Assistant Professor of Medicine (Oncology)
Bio Dr. 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.