Thursday, August 2, 2018
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.
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.
Thursday, March 29, 2018
Alex Fuksenko, a senior at the University of Maryland in College Park, spent his summer in the lab of NIH IRP Investigator Kevin Briggman, Ph.D.
Fuksenko helped to create a website called Labrainth that “gamifies” the identification and tracing of neurons in 2D images produced by electron microscopes. By visiting the website and completing those activities, members of the public can earn points and move up leaderboards while producing data that machine learning algorithms can use to learn how to trace neurons in these images themselves, a necessary step towards producing an accurate 3D model of the human brain.
Wednesday, March 7, 2018
Once confined to the realms of science fiction, virtual reality (VR) has crossed over into the real world in a wide array of fields, including scientific research and clinical medicine. In the IRP, several researchers are utilizing the cutting-edge technology in their efforts to improve human health.
Susan Persky, Ph.D., for instance, runs the Immersive Virtual Environment Test Unit, where she uses VR to simulate how genetic information might affect doctor-patient interactions and influence patients’ emotions, beliefs, and decisions. She has also put the technology to use studying the food choices of overweight and obese individuals by presenting them with a simulated buffet. Meanwhile, John Ostuni, Ph.D., explores how VR might help doctors diagnose or treat patients, such as by providing access to physical therapy without going to the hospital. And Victor Cid, M.S., creates virtual reality scenarios for the Disaster Information Management Research Center that can train emergency personnel how to more effectively respond to major crises.
On Friday, February 23, they joined several NIH colleagues for a Reddit “Ask Me Anything” (AMA) to answer questions from the public about how virtual reality might change the way medicine and research are practiced and ultimately make people’s lives better. Read on for some of the most interesting exchanges that took place or check out the full AMA on Reddit.