Research from Italy to be presented at this year's European Congress on Obesity (ECO 2026, Istanbul, Türkiye, 12–15 May) and published in the journal Nutrients shows that when the gold standard ...

A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results predicted a patient's risk of hepatocellular carcinoma (HCC), the most common ...

CHICAGO -- Classifying inflammatory subphenotypes of acute respiratory distress syndrome (ARDS) with bedside lab testing was ...

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

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 ...

Representative images of bacterial microcolonies and food debris captured using a phase-contrast microscope during research by Luyao Ma at Oregon State University. Researchers have significantly ...

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

Researchers at örebro University have developed two new AI models that can analyze the brain's electrical activity and accurately distinguish between healthy individuals and patients with dementia, ...

1 School of Computing and Data Science, Wentworth Institute of Technology, Boston, USA. 2 Department of Computer Science and Quantitative Methods, Austin Peay State University, Clarksville, USA. 3 ...