
Biomedical research: deep learning outperforms machine learning
Deep-learning methods have the potential to offer substantially better results, generating superior representations for characterizing the human brain.
Deep-learning methods have the potential to offer substantially better results, generating superior representations for characterizing the human brain.
Scientists have proposed a new principle by which active matter systems can spontaneously order, without need for higher level instructions or even programmed interaction among the agents.
Using a device that could be built with a dollar's worth of open-source parts and a 3D-printed case, researchers want to help the hundreds of millions of older people worldwide who can't afford existing hearing aids to address their age-related hearing loss.
Researchers have found a way to send tiny, soft robots into humans, potentially opening the door for less invasive surgeries and ways to deliver treatments for several conditions.
A new machine learning–based online tool allows for early detection of COVID-19 outbreaks in different U.S. counties.
Scientists have used machine learning to predict the reemergence of existing infectious diseases.
Scientists and collaborators are using machine learning to address two key barriers to industrialization of two-photon lithography.
Researchers at Georgia Tech have now developed a chip that accurately replicates its function using the human cells that form this important part of our anatomy.
Using a virtual reality simulation to show how flu spreads and its impact on others could be a way to encourage more people to get a flu vaccination.
Combining new wearable electronics and a deep learning algorithm could help disabled people wirelessly interact with a computer.
The Open-Source Bionic Leg will enable investigators to efficiently solve challenges associated with controlling bionic legs across a range of activities in the lab and out in the community.