A study led by UC Riverside researchers offers a practical fix to one of artificial intelligence's toughest challenges by ...
MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data ...
Dr Michele Orini shares how machine learning can help identify critical VT ablation targets for a safer, data-driven ...
Machine learning can help predict whether people newly diagnosed with MS will experience disability worsening that occurs ...
An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ...
Researchers have employed Bayesian neural network approaches to evaluate the distributions of independent and cumulative ...
Since 2021, Korean researchers have been providing a simple software development framework to users with relatively limited AI expertise in industrial fields such as factories, medical, and ...
However, NGD faces several challenges associated with gamma-ray generation and attenuation complexities. Unlike GGD, which utilizes 0.662 MeV monoenergetic γ rays from a 137 Cs source, NGD employs ...
A rotating cylinder with its side cut away to expose the core, showing patches of purple, blue, green, yellow, and orange that are dense in the middle and more diffuse toward the edges. This rotating ...
Artificial intelligence startup OpenEvidence says its AI model has scored a perfect 100% on the United States Medical Licensing Examination (USMLE), raising the bar on the proficiency of AI models to ...
Objective: We aim to investigate the factors influencing enteral nutrition feeding intolerance (ENFI) in critically ill patients and develop a risk prediction model for ENFI in intensive care unit ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In this research work authors have experimentally validated a blend of Machine ...