School of Medicine


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  • Michael Gensheimer

    Michael Gensheimer

    Clinical Associate Professor, Radiation Oncology - Radiation Therapy

    Current Research and Scholarly InterestsIn addition to my clinical research in head and neck and lung cancer, I work on the application of computer science and machine learning to cancer research. I develop tools for analyzing large datasets to improve outcomes and safety of cancer treatment. I developed a machine learning prognostic model using data from around 13,000 patients with metastatic cancer which performs better than traditional models and physicians [PubMed ID 33313792]. We recently completed a prospective randomized study in thousands of patients in which the model was used to help improve advance care planning conversations.

    I also work on the methods underpinning observational and predictive modeling research. My open source nnet-survival software that allows use of neural networks for survival modeling has been used by researchers internationally. In collaboration with the Stanford Research Informatics Center, I examined how electronic medical record (EMR) survival outcome data compares to gold-standard data from a cancer registry [PubMed ID 35802836]. The EMR data captured less than 50% of deaths, a finding that affects many studies being published that use EMR outcomes data.

  • Alireza Ghiam, MD, MS

    Alireza Ghiam, MD, MS

    Clinical Associate Professor, Radiation Oncology - Radiation Therapy

    BioDr. Ghiam is an American and Canadian Board-Certified Radiation Oncologist with the Stanford Medicine Cancer Center and a Clinical Associate Professor in the Department of Radiation Oncology at Stanford University School of Medicine. After completing an MSc in Molecular Biology & Genetics at the University of Montreal, he completed a residency in Radiation Oncology and fellowship in Head & Neck and GU radiation oncology at the University of Toronto.

    He diagnoses and treats various conditions specializing in head & neck cancer, genitourinary malignancies, and metastatic disease. His treatment expertise includes oligometastatic disease, palliative radiation therapy, stereotactic ablative radiotherapy, and proton therapy.

    Dr. Ghiam has contributed to the field through his authorship of technology- and biology-based publications and collaboration in clinical trials. He has been recognized by awards from the American Society for Radiation Oncology (ASTRO), the Canadian Association of Radiation Oncology (CARO), and the Universities of Toronto and Pennsylvania. In recognition of his educational work, he received two prestigious teaching awards for teaching residents and medical students. He has presented his research work nationally and internationally and authored and co-authored several papers.

    Dr. Ghiam's interest lies in exploring novel AI-powered technologies that can enhance patient outcomes, and bridge health equity gaps in radiation oncology. He is also interested in clinical trials of innovative radiation therapy techniques with a focus on leveraging technology and biology to reduce toxicity and increase precision.

    Dr. Ghiam is dedicated to academia, education, and diversity. He is committed to improving patient outcomes and changing the role of supportive care in radiation oncology by promoting quality standards and utilizing palliative radiotherapy to enhance the quality of life for his patients.

    Dr. Ghiam practices evidence-based care with compassion and treats his patients as he would his own family.

  • Iris C. Gibbs, MD, FACR, FASTRO

    Iris C. Gibbs, MD, FACR, FASTRO

    Professor of Radiation Oncology (Radiation Therapy) and, by courtesy, of Neurosurgery

    Current Research and Scholarly InterestsDr. Gibbs is a board-certified radiation oncologist who specializes in the treatment of CNS tumors. Her research focuses on developing new radiation techniques to manage brain and spinal tumors in adults and children. Dr. Gibbs has gained worldwide acclaim for her expertise in Cyberknife robotic radiosurgery.