Why today’s AI systems struggle with consistency, and how emerging world models aim to give machines a steady grasp of space ...

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

The workflow encompasses patient datacollection and screening, univariate regression analysis for initial variable selection, systematic comparison of 91 machine learning models,selection and ...

Abstract: Feature representation is a key factor in machine learning-based malware detection, affecting the information expressed and used for detection, the choice of the classifier, and ...

Abstract: The risk of pedestrian-involved traffic accidents represents a significant challenge to road safety and necessitates objective methods for analyzing the contributing factors. This study ...

Community health outcomes significantly impact older populations' wellbeing and quality of life. Traditional analytical methods often struggle to accurately predict health risks at the community level ...

ABSTRACT: Missing data remains a persistent and pervasive challenge across a wide range of domains, significantly impacting data analysis pipelines, predictive modeling outcomes, and the reliability ...

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 ...

SAVANA uses a machine learning algorithm to identify cancer-specific structural variations and copy number aberrations in long-read DNA sequencing data. The complex structure of cancer genomes means ...

Discovering faster algorithms for matrix multiplication remains a key pursuit in computer science and numerical linear algebra. Since the pioneering contributions of Strassen and Winograd in the late ...