A deep-learning model developed using serial image scans of tumors from patients with non-small cell lung cancer (NSCLC) predicted treatment response and survival outcomes better than standard clinical parameters.
Engineers at Duke University are developing a smart robotic system for sniffing out pollution hotspots and sources of toxic leaks. Their approach enables a robot to incorporate calculations made on the fly to account for the complex airflows of confined spaces rather than simply 'following its nose.'
Harmonization method developed to reduce site-related differences between neuroimaging data from individual imaging sites and publicly released big data of multiple psychiatric disorders from many imaging sites.
A new learning system developed by MIT researchers improves robots' abilities to mold materials into target shapes and make predictions about interacting with solid objects and liquids. The system, known as a learning-based particle simulator, could give industrial robots a more refined touch -- and it may have fun applications in personal robotics, such as modelling clay shapes or rolling sticky rice for sushi.
Researchers at the US Army Combat Capabilities Development Command's Army Research Laboratory, the Army's corporate research laboratory also known as ARL, and Towson University may have identified a new way to improve network security.
UCLA researchers have developed a new artificial intelligence system to help radiologists improve their ability to diagnose prostate cancer.
Insect-inspired arm technology from Purdue University aims to improve drones to handle larger payloads.
Farmers can't predict their annual corn harvest with certainty, but with the help of new research from Michigan State University, they can now pinpoint specific parts of their fields that consistently produce either good or bad yields. Not only will this save them time and money; it will solve one of the most widespread environmental problems facing crop-producing regions -- nitrogen loss.
In liquid crystals, molecules automatically arrange themselves in an ordered fashion. Researchers from the University of Luxembourg have discovered a method that allows an anti-ordered state, which will enable novel material properties and potentially new technical applications, such as artificial muscles for soft robotics. They published their findings in the scientific journal Science Advances.
Georgia Institute of Technology researchers, in collaboration with Cornell University and University of Kentucky, have developed an artificially intelligent (AI) agent that can automatically generate natural language explanations in real-time to convey the motivations behind its actions.