Session Chair Profile

Ph.D., Vice Chair of Research, Radiology, UCSF

Sharmila Majumdar’s research work on imaging, particularly magnetic resonance and development of image processing and analysis tools, has been focused in the areas of osteoporosis, osteoarthritis, orthopedic imaging, and lower back pain. Her more recent focus has been on artificial intelligence applied to biomedical imaging. Her research is supported by grants from the NIH and corporate entities, and is diverse – ranging from technical development to clinical trials. She was selected as a fellow of the American Institute of Medical and Biological Engineers in 2004 and a fellow of the International Society of Magnetic Resonance in Medicine in 2008. In 2007, the UCSF Haile T. Debas Academy of Medical Educators at UCSF awarded her the “Excellence in Direct Teaching and/or Excellence in Mentoring and Advising Award”. She was awarded the ISMRM Gold medal in 2016. She has published extensively in highly regarded journals and serves as a reviewer and on the Editorial Board of multiple scientific journals.

 Session Abstract – PMWC 2020 Silicon Valley

One of the most promising areas of health innovation is the application of artificial intelligence, machine learning, and deep learning primarily in medical imaging. The increase in the amount of data and the possibility to use ML/DL to identify findings either detectable or not by the human eye, radiology is now moving from a subjective perceptual skill to more objective science. Radiologists, who were at the forefront of the digital era in medicine, can guide the introduction of AI solutions that accommodate ethical and regulatory requirements into healthcare.