South Korean researchers have developed a guided-learning framework that accurately predicts PV power without requiring irradiance sensors during operation, using routine meteorological data instead.

The UNLV Runnin' Rebels have a must-win game tonight on the road against the Fresno State Bulldogs. UNLV has dropped three games in a row, and are now looking t ...

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...

Clinical and health care resource use burden were greater among patients with diagnosed hypereosinophilic syndrome or predicted hypereosinophilic syndrome via machine learning vs. those without the ...

A machine learning model trained on EEG data from patients recovering from strokes helps predict how new patients will regain ...

Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...

Scientists have created an AI model that forecasts moderate heat stress—a major precursor to coral bleaching—at sites along ...

Scientists have created an AI model that forecasts moderate heat stress — a major precursor to coral bleaching — at sites ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...

Cardiovascular disease continues to be the leading cause of death worldwide. To save lives, constantly improving diagnostic ...

Abstract: This study explores the predictive capacity of financial asset returns in forecasting macroeconomic regime shifts, specifically the transition among Inflation, Expansion, Stagflation, and ...

Scientists at UC San Diego revealed a new platform intended to translate data-driven academic disease forecasting into ...