Noninvasive Nerve Stimulator May Ease Sleep Apnea
Using a transcutaneous electrical neurostimulator (TENS) machine may reduce the severity of obstructive sleep apnea (OSA) in people not adhering to continuous positive airway pressure (CPAP) therapy, a small single-center randomized trial suggested. After 3 months, the difference in apnea/hypopnea index (AHI) scores in unadjusted analysis significantly favored the TENS group versus the usual-care group […]
Virtual reality game to objectively detect ADHD
Researchers have used virtual reality games, eye tracking and machine learning to show that differences in eye movements can be used to detect ADHD, potentially providing a tool for more precise diagnosis of attention deficits. Their approach could also be used as the basis for an ADHD therapy, and with some modifications, to assess other […]
Seeing how odor is processed in the brain: New study shows odor unpleasantness processed more quickly than perceived quality
A specially created odor delivery device, along with machine learning-based analysis of scalp-recorded electroencephalogram, has enabled researchers at the University of Tokyo to see when and where odors are processed in the brain. The study found that odor information in the brain is unrelated to perception during the early stages of being processed, but when […]
New machine learning method to analyze complex scientific data of proteins: Method allows faster and more accurate data analysis from NMR spectrometers
Scientists have developed a method using machine learning to better analyze data from a powerful scientific tool: nuclear magnetic resonance (NMR). One way NMR data can be used is to understand proteins and chemical reactions in the human body. NMR is closely related to magnetic resonance imaging (MRI) for medical diagnosis. NMR spectrometers allow scientists […]
New framework applies machine learning to atomistic modeling: Method could lead to more accurate predictions of how new materials behave at the atomic scale
Northwestern University researchers have developed a new framework using machine learning that improves the accuracy of interatomic potentials — the guiding rules describing how atoms interact — in new materials design. The findings could lead to more accurate predictions of how new materials transfer heat, deform, and fail at the atomic scale. Designing new nanomaterials […]
Machine learning tool sorts the nuances of quantum data
An interdisciplinary team of Cornell and Harvard University researchers developed a machine learning tool to parse quantum matter and make crucial distinctions in the data, an approach that will help scientists unravel the most confounding phenomena in the subatomic realm. The Cornell-led project’s paper, “Correlator Convolutional Neural Networks as an Interpretable Architecture for Image-like Quantum […]