Researchers have successfully rebuilt the bridge between experimental neuroscience and advanced artificial intelligence learning algorithms. Conducting new types of experiments on neuronal cultures, the researchers were able to demonstrate a new accelerated brain-inspired learning mechanism. When the mechanism was utilized on the artificial task of handwritten digit recognition, for instance, its success rates substantially outperformed…

Researchers have upgraded a key computer code for calculating forces acting on magnetically confined plasma in fusion energy experiments. The upgrade will help scientists further improve the design of breakfast-cruller-shaped facilities known as stellarators. The revised software lets researchers more easily determine the boundary of plasma in stellarators. When used in concert with two other…

Researchers have developed a new automatized way to localize mandibular canals. The lower jaw is an anatomically complex structure and medical experts use X-ray and computer tomography (CT) models to detect and diagnose such structures. Typically, dentists and radiologists define the location of the mandibular canals manually from the X-ray or CT scans, which makes…

Compared to standard machine learning models, deep learning models are largely superior at discerning patterns and discriminative features in brain imaging, despite being more complex in their architecture. Advanced biomedical technologies such as structural and functional magnetic resonance imaging (MRI and fMRI) or genomic sequencing have produced an enormous volume of data about the human…

A form of artificial intelligence designed to interpret a combination of retinal images was able to successfully identify a group of patients who were known to have Alzheimer’s disease, suggesting the approach could one day be used as a predictive tool, according to an interdisciplinary study. The novel computer software looks at retinal structure and…

A team of scientists have found that artificial intelligence can predict risk of new atrial fibrillation (AF) and AF-related stroke. Atrial fibrillation is the most common cardiac arrhythmia and is associated with numerous health risks, including stroke and death. The study, published in Circulation, used electrical signals from the heart — measured from a 12-lead…

Artificial intelligence is being used for many extremely complex tasks. So why not use machine learning to study particle physics? As it turns out, this is not easy, because of some special mathematical properties of particle physics. But now, a neural network has been developed that can be used to study quark gluon plasma —…

Researchers are working with community leaders to develop a mobile alert app to help locate missing people with dementia. Noelannah Neubauer, a postdoctoral fellow at the University of Waterloo’s School of Public Health Sciences, said «Community ASAP» is aimed at addressing a gap in available tools when it comes to alerts for missing older adults…

Chemical engineers have trained a neural network model to plan synthetic routes to any target molecule, optimizing user-specified objectives such as cost, time, and sustainability. Organic chemists generally work backwards from the target molecule to the starting materials using a process called retrosynthetic analysis. During this process, the chemist faces a series of complex and…

Researchers have developed a method to validate test drives through highly realistic driving simulation studies and to substantially simplify the approval process for automated driving systems. New regulation as initial spark Recently, because the first global regulation for Automated Lane Keeping Systems (ALKS) has been in force since the beginning of 2021. This law resolves…