Speaker Profile
M.D., MSCI, Assistant Professor, University of Washington
Biography
Aaron Y. Lee MD MSCI is focused on the translation of novel computation techniques including deep learning for automated diagnosis and to uncover new pathophysiologic mechanisms in routine clinical data from large electronic health databases. His main areas of research include age-related macular degeneration, diabetic eye disease, and macular telangiectasia. He has published over 50 peer reviewed manuscripts and editorials. Dr. Lee is an assistant professor and vitreoretinal surgeon at University of Washington, Department of Ophthalmology. He has served on the American Academy of Ophthalmology Medical Information Technology Committee and the American Academy of Ophthalmology IRIS Analytics Task Force. Dr. Lee received his BA in Biochemistry from Harvard University. He then completed his MD and Masters of Science in Clinical Investigations from the Washington University of St Louis. After an internship at St. John’s hospital, he returned to Washington University to complete his ophthalmology residency. He then completed two fellowships: a medical retina fellowship at Moorfields Eye Hospital in London, and a vitreoretinal surgical fellowship at the University of British Columbia in Vancouver Canada.
AI and Data Sciences Showcase: University of Washington
The UW is one of the world’s preeminent public universities. Our impact on individuals, our region and the world is profound — whether we are launching young people into a boundless future or confronting the grand challenges of our time through undaunted research and scholarship.
Applications Of Artificial Intelligence With Ophthalmic Imaging
The dawn of the machine learning era has caused an explosion of deep learning models applied to almost every aspect of ophthalmic care. Despite significant real-world limitations, these technologies are poised to play a disruptive role in the delivery of eye-care worldwide.
Session Abstract – PMWC 2020 Silicon Valley
Session Synopsis: In order to expedite clinical diagnostics and advance precision patient care, innovative developments in algorithm development and imaging sciences, combined with improved understanding of the complex biology of cancer is crucial. This session will cover various developments, needs, and opportunities of expedited clinical decision-making.