Both approaches identified hemoglobin as one of the most significant predictors of CKD risk. Additional top-ranked features included blood urea, sodium levels, red blood cell count, potassium, and ...

More than half of transplant recipients in a large analysis developed chronic graft-versus-host disease, and 15% died from ...

Technology is revolutionising how we gather and assess data on nature, presenting huge benefits and no little irony ...

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...

By transforming everyday smartphone signals into high-resolution mobility data, researchers have reconstructed how residents of Cuenca travel across the city and what those patterns mean for energy ...

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...

A publicly available AI tool correctly predicted approximately twice as many children with acute lymphoblastic leukemia who would relapse as three expert clinicians.XGBoost, a boosting algorithm, had ...

Birdwatching activates a rare cognitive pattern called soft fascination — a state where attention is gently engaged without ...

Machine-learning hedge funds surged on the recent jump in precious metals prices, before sidestepping last week's sell-off. Also known as commodity trading advisors (CTAs), the sector notched up one ...

Researchers have developed an advanced artificial intelligence (AI) framework designed to significantly improve the forecasting of carbon dioxide emissions in the aviation sector. ACGRIME is an ...

Oracle-based quantum algorithms cannot use deep loops because quantum states exist only as mathematical amplitudes in Hilbert space with no physical substrate. Criticall ...

These early AI-generated images looked impressive at first glance… until you noticed the extra fingers, warped faces, and ...