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 ...
Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...
A research paper by scientists from Beihang University proposed a machine learning (ML)-driven cerebral blood flow (CBF) prediction model, featuring multimodal imaging data integration and an ...
Advanced fraud detection system using machine learning to identify fraudulent transactions and activities. This project implements multiple machine learning algorithms including Random Forest, XGBoost ...
Abstract: Random forest (RF) is widely regarded as one of the most prevalent machine learning algorithms. To achieve higher precision, the structure of decision trees that serve as base learners in RF ...
Abstract: Research and development of highly accurate falling detection systems (FDSs) for individuals with medical conditions or the elderly are crucial for mitigating the risks associated with falls ...
Background: Inflammatory bowel disease (IBD) poses significant mortality risks for critically ill patients requiring intensive care unit (ICU) admission, driven by complications such as malnutrition, ...
ABSTRACT: The advent of the internet, as we all know, has brought about a significant change in human interaction and business operations around the world; yet, this evolution has also been marked by ...
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