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I am Intramural Blog

big data

Mining Medical Data to Improve COVID-19 Treatment

Study Reveals Medications Associated With Lower Odds of Severe Infection

Tuesday, June 28, 2022

doctor typing on laptop

Many researchers studying COVID-19 have spent the past two years poring over test tubes and isolated cells. However, large troves of data about people’s interactions with the healthcare system can also be a rich source of useful insights. Using one such database, IRP researchers found that older adults taking certain medications were less likely to catch COVID or experience severe repercussions from the virus.

Three Billion Base Pairs vs. One Powerful Computer

Tuesday, November 27, 2018

a stand of DNA

The human genome comprises roughly three billion base pairs and around 20,000 protein-coding genes, according to recent estimates. That’s a lot of information crammed into the tiny nucleus of a cell, and it doesn’t even include the many genes that do not produce a protein or the fact that most genes come in multiple flavors that vary in different individuals. Add to that the phenomenon of an identical gene being either more or less active in two different people and you can quickly end up with genomic datasets that would overload nearly any computer. Fortunately for IRP senior investigator Daniel Levy, M.D., the NIH IRP has one of the few computer systems in the world that can handle this mountain of information.

Top-of-the-Line Supercomputer Turbocharges NIH Research

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.

NIH's supercomputer, Biowulf

Challenges to Training Artificial Intelligence with Medical Imaging Data

Tuesday, November 1, 2016

Example artificial intelligence disease detection from radiology images, NIH IRP, cropped

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?

Robot Superheroes to Big 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.

Hoo-Chang Shin and Holger Roth

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