Wednesday, June 13, 2018
Access to robust computing resources provides a critical foundation for advancing the wide variety of biomedical research taking place within the NIH’s Intramural Research Program (IRP). Whether performing molecular modeling simulations, generating whole-genome sequencing data, deducing the structures of biomolecules, or advancing drug discovery efforts, our ability to analyze large-scale biological and biomedical data strongly depends on our ability to employ computationally intensive approaches that produce interpretable results and advance translational efforts aimed at improving human health.
Tuesday, November 1, 2016
If you were going to train an artificial intelligence (AI) system to understand and accurately diagnose medical images, what kind of information do you think would be most effective: lots of general image data, or small amounts of specific data?
Monday, May 18, 2015
As a child I liked robots. Growing up in Korea, I liked cartoons and movies where people were on a mission to save the world with the robots they invented, and I wanted to develop a superhero robot someday, too. While my robot isn’t yet complete, the path I followed in pursuit of my goals eventually led me to explore data analysis.
And here I am, a postdoc at the NIH—probably the largest healthcare research institution in the world—in the Imaging Biomarkers and Computer-Aided Diagnosis Laboratory led by Dr. Ronald M. Summers. Our lab is part of the Department of Radiology and Imaging Sciences at the NIH Clinical Center.