Advances in artificial intelligence (AI) are now opening new possibilities for faster and more accurate flood mapping, enabling researchers to process large volumes of environmental data and satellite ...

A new study suggests that lenders may get their strongest overall read on credit default risk by combining several machine learning models rather than relying on a single algorithm. The researchers ...

The promise of artificial intelligence in credit scoring is undeniable. By analyzing vast, non-traditional datasets from ...

Medicaid managed care organizations should prioritize children in low-opportunity neighborhoods to optimize health care utilization, improve minority health, and address health-related social needs.

Objectives To evaluate whether type 2 diabetes mellitus (T2DM) presence and severity are associated with differences in global and domain-specific cognitive function among US adults, using ...

A new machine learning model built using a simple and interpretable approach predicts in-hospital death in patients with acute liver failure and reveals top risk drivers.

Background Remission and low-disease activity are recommended targets in systemic lupus erythematosus (SLE), yet many ...

1 Department of Computer and Instructional Technologies Education, Gazi Faculty of Education, Gazi University, Ankara, Türkiye. 2 Department of Forensic Informatics, Institute of Informatics, Gazi ...

Abstract: Voltage sag, swell, harmonics, and transients are power quality (PQ) disturbances that damage modern electrical apparatus. This paper presents an effective classification approach using ...

Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...

Abstract: Memory-based malware is a cyber threat that operates directly in system memory without creating permanent files, making detection through conventional signature-based methods difficult. This ...