Abstract: Artificial intelligence driven by deep learning have attracted much attention in the past several years and holds significant potential for improved healthcare.  The enormous success of deep learning stems from its unique capabilities of extracting and aggregating essential features from big data and then making inferences.  In this talk, I will summarize recent advances in AI applications in imaging and therapy, interpretable AI, identify the pitfalls of current data-driven approaches, and provide my perspectives on the future of AI in biomedical physics and medicine.  

About the speaker: Lei Xing, PhD is a Jacob Haimson & Sarah S. Donaldson Professor of Medical Physics at Stanford University and Director of the Medical Physics Division in the Radiation Oncology Department. Dr. Xing’s research has been focused on artificial intelligence in medicine, medical imaging, treatment planning, image guided interventions, nanomedicine, and applications of molecular imaging in radiation oncology. Dr. Xing is an author on more than 400 peer reviewed publications, a co-inventor on many issued and pending patents, and a co- investigator or principal investigator on numerous NIH, NSF, DOD, RSNA, ACS and many corporate grants. Dr. Xing will speak on the future of AI in radiation oncology.