MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data ...
A new artificial intelligence (AI) method called BioPathNet helps researchers systematically search large biological data ...
Dr Michele Orini shares how machine learning can help identify critical VT ablation targets for a safer, data-driven ...
Implementing an Electrocardiogram Suite in the Emergency Department to Decrease Door-to-EKG Time ...
Why today’s AI systems struggle with consistency and how emerging world models aim to give machines a steady grasp of space ...
Assistant Professor Yupeng Zhang and his team, along with researchers from the University of California, Irvine, received a ...
Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
Morning Overview on MSN
Scientists build a ‘periodic table’ for AI models
Scientists are trying to tame the chaos of modern artificial intelligence by doing something very old fashioned: drawing a table. Instead of chemical elements, the new chart arranges learning ...
Accurate smartphone positioning in dense urban environments remains challenging due to signal blockage, multipath effects, and unreliable satellite visibility. This study presents a new positioning ...
Abstract: In this article, we utilize the concept of average controllability in graphs, along with a novel rank encoding method, to enhance the performance of Graph Neural Networks (GNNs) in social ...
According to Greg Brockman, a co-founder of OpenAI, a critical yet often overlooked skill in machine learning is the ability to extract meaningful insights from minor fluctuations or 'small wiggles' ...
Abstract: Graph classification is essential for understanding complex biological systems, where molecular structures and interactions are naturally represented as graphs. Traditional graph neural ...
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