Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

A novel multi-task XGBoost model shows robust overall performance in predicting antimicrobial resistance in common gram-negative pathogens.

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

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

The UNLV Runnin' Rebels could knock off the Fresno State Bulldogs tonight, but it won't be easy.

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

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 ...

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 ...

Recent study reveals machine learning's potential in predicting the strength of carbonated recycled concrete, paving the way ...

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

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 ...

Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...