Machine learning algorithms help computers analyse large datasets and make accurate predictions automatically.Classic models ...

Large language models (LLMs) can generate credible but inaccurate responses, so researchers have developed uncertainty quantification methods to check the reliability of predictions. One popular ...

Hydrological models represent water movement in natural systems, and they are important for water resource planning and ...

Dr. Amy Baird, Professor of Biology at the University of Houston-Downtown (UHD), and her colleagues are seeking to change the ...

This illustrates a widespread problem affecting large language models (LLMs): even when an English-language version passes a ...

Combined assessment using MSUS semiquantitative scores and inflammatory biomarkers may improve diagnostic accuracy and ...

Objective To estimate the prevalence of potential overtreatment of type 2 diabetes mellitus (T2DM) among older adults and to develop and compare predictive models to identify patient and physician ...

Advances in artificial intelligence (AI) are now opening new possibilities for faster and more accurate flood mapping, ...

Objective Geriatric patients often face issues related to polypharmacy and adverse drug events. Re-evaluating prescribed ...

There was a time when American shooters were not very fond of rifle cartridges with “mm” in their names. The 7mm Remington Magnum helped change that attitude when it was introduced 64 years ago ...

Abstract: Fuzzy classification models are important for handling uncertainty and heterogeneity in high-dimensional data. Although recent fuzzy logistic regression approaches have demonstrated ...