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 deep learning model using retinal images obtained during ROP screening may be used to predict diagnosis of BPD and PH.

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 ...

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

Researchers develop an AI tool to predict cardiometabolic multimorbidity risk in type 2 diabetes, aiding early intervention and personalised care. Find out more.

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 ...

Fungi are the hidden architects of our ecosystems, acting as everything from helpful partners for plants to aggressive ...

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

The Law of Mass action predicts that all adverse drug reactions are related to the concentration of the drug at the site of ...