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

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 ...

In the United States: The Equal Credit Opportunity Act (ECOA) and the Fair Credit Reporting Act (FCRA) require lenders to ...

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 ...

Background Cardiovascular disease (CVD) is the leading cause of mortality worldwide, while depression is highly prevalent in this patient population and has long been regarded as an independent risk ...

Abstract: In this project, we aimed to assess mushroom contamination by analyzing images using two different algorithms: a novel K-Nearest Neighbour algorithm and a traditional Logistic Regression ...

On Nov. 7, 2017, the American social-media platform Reddit shut down r/Incels, an online forum with more than 40,000 members. This was in line with a new policy the company brought in, banning content ...

This study explores the feasibility of using breathomic biomarkers analyzed by machine learning as a non-invasive diagnostic tool to differentiate between benign and malignant thoracic lesions, aiming ...