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

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 ...

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 ...

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 ...

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...

Abstract: The rapid development of the modern world has increased the use of social media. One of the most popular social media platforms in Indonesia is X, where users can share tweets to express ...

Abstract: The abstract is an imperfect defect detection model meant to classify various defects of castings. It presents an excellent precision, recall, and $\mathbf{F 1}$-score of six classes of ...