Note: This video may require joining the NVIDIA Developer Program or login

GTC Silicon Valley-2019 ID:S9876:Developing a Roadmap for Machine Learning in Clinical Radiology

Christopher Hess(University of California, San Francisco)
We will outline strategies designed to incorporate emerging artificial intelligence and machine learning into the clinical practice of diagnostic radiology, the primary entry point for imaging in the U.S. healthcare system. We'll discuss the underlying radiology value chain to explain the architecture of existing radiology information management systems for imaging. We will highlight the centrality of imaging in guiding patient care to outline the opportunities and barriers to adopting AI and ML in clinical practice, and we'll explore how AI and ML are poised to transform imaging delivery for certain medical domains to the benefit of patients.