Recorded on April 17, 2024, by the Stanford Center for Artificial Intelligence in Medicine and Imaging (AIMI) and Stanford Integrative Biomedical Imaging Informatics at Stanford (IBIIS).

Abstract: AI for healthcare has the potential to revolutionize how we practice medicine. However, to do this in a fair and trustworthy manner requires special attention to how AI models work and their potential biases. In this talk, I will cover the considerations for building AI systems that improve healthcare.

Bio: Roxana Daneshjou, MD, PhD, studied Bioengineering at Rice University before matriculating to Stanford School of Medicine where she completed her MD and a PhD in Genetics with Dr. Russ Altman as part of the medical scientist training program. She completed dermatology residency at Stanford as part of the research track and completed a postdoc in Biomedical Data Science with Dr. James Zou. She currently is the assistant director of the Center of Excellence for Precision Heath & Pharmacogenomics, director of informatics for the Stanford Skin Innovation and Interventional Research Group (SIIRG), a founding member of the Translational AI in Dermatology (TRAIND) group, and a faculty affiliate of Humancentered Artificial Intelligence (HAI) Institute and the Center for AI in Medicine and Imaging (AIMI).