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I am Intramural Blog

radiology

Doctor Data: How Computers Are Invading the Clinic

Thursday, August 2, 2018

human silhouette surrounding a computer network

For most of their history, computers have been limited to mindlessly executing the instructions their programmers give them. However, recent advances have given rise to the intertwined fields of artificial intelligence (AI) and machine learning, which focus on the creation of computer programs that can operate independently and even teach themselves to perform specific, specialized tasks. In 2013, the online PubMed database listed only 200 research publications related to ‘deep learning,’ a new type of machine learning that has shown success for particularly difficult tasks like object and speech recognition. Just four years later, in 2017, that number exceeded 1,100.

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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