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

This illustrates a widespread problem affecting large language models (LLMs): even when an English-language version passes a safety test, it can still hallucinate dangerous misinformation in other ...

New paired studies from the University of Minnesota Twin Cities show that machine learning can improve the prediction of floods. The studies, published in Water Resources Research and the Proceedings ...

AI-focused accounting ERP provider DualEntry tested some of the most popular AI models on various accounting workflows and found that, at best, they're 77.3% accurate.

Listeria is the third-leading cause of death among bacterial foodborne pathogens in the U.S. and pregnant individuals bear a disproportionate share of that burden.

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 medications and considering deprescribing is critical. Medication discrepancies ...

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