A team of scientists from Geisinger and Tempus have found that artificial intelligence can predict risk of new atrial fibrillation (AF) and AF-related stroke.
A researcher from Kanazawa University devised a way to speed up a fundamental task in computer vision and graphics known as non-rigid point set registration. Unlike previous registration techniques, the proposed method is computationally efficient even for large data sets. Moreover, the computing times for this method are shorter than those for a state-of-the-art approach. The results of this study could have implications for various fields, such as autonomous driving, medical imaging, and robotic manipulation.
In a JAMA Network Open article, Traverso and colleagues report the results of a national survey and a cohort study in an emergency department (ED), which analyzed patients' satisfaction with an initial evaluation conducted by a robotic system. Overall, 92.5 percent of patients were accepting of and satisfied with their experience.
For practical problem-solving, AI researchers need to look beyond their field and collaborate with social scientists and other domain experts, SMU professors concurred at a GYSS 2021 panel.
Cyber-physical systems (CPS), which combine modern networking with physical actuators, can be vulnerable against hackers. Recently, researchers at DGIST developed a new framework for CPSs that is resilient to a sophisticated kind of cyberattack. Unlike existing solutions, the proposed approach allows for real-time detection and recovery from the attack while ensuring stable operation. This paves the way for secure and reliable CPSs across various application domains, such as smart cities and unmanned public transportation.
A large majority of patients interacting with a health care provider via a video screen mounted on a robot said it was similar to an in-person interaction with a health care worker. The work was led by MIT and Brigham and Women's Hospital.
Researchers evaluated the feasibility and acceptability of using a mobile robotic system to perform health care tasks such as acquiring vital signs, obtaining nasal or oral swabs and facilitating contactless triage interviews of patients with potential COVID-19 in the emergency department.
In "Subverting Privacy-Preserving GANs: Hiding Secrets in Sanitized Images," researchers at the NYU Tandon School of Engineering led by Siddharth Garg, professor of electrical and computer engineering, explored whether private data could still be recovered from images that had been "sanitized" by such deep-learning discriminators as privacy protecting GANs (PP-GANs).
A POSTECH joint research team demonstrates highly efficient 3D nano-imaging with XFEL and machine learning.
MIT researchers have simulated a soft-bodied robot that turns rigid on demand. The advance may help broaden robots' range of tasks and allow for safe interactions with people, including in patient care settings.