Objective To examine whether a multicomponent commercial fitness app with very small (‘micro’) financial incentives (FI) ...

A research paper by scientists from Beihang University proposed a machine learning (ML)-driven cerebral blood flow (CBF) prediction model, featuring multimodal imaging data integration and an ...

What if artificial intelligence could turn centuries of scientific literature—and just a few lab experiments—into a smarter, ...

A study conducted by experts from the University of the Philippines-Diliman showed that logistic regression is a reliable model for predicting the performance of licensure examination takers. Released ...

Williams, A. and Louis, L. (2026) Cumulative Link Modeling of Ordinal Outcomes in the National Health Interview Survey Data: Application to Depressive Symptom Severity. Journal of Data Analysis and ...

Introduction Armed conflict severely impacts health, with indirect deaths often exceeding direct casualties two to four times ...

Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.

In the swiftly evolving tech landscape, Artificial Intelligence (AI) and Machine Learning (ML) have emerged as two of the most ...

Researchers have successfully demonstrated quantum speedup in kernel-based machine learning. When you purchase through links on our site, we may earn an affiliate commission. Here’s how it works.

As one of the important statistical methods, quantile regression (QR) extends traditional regression analysis. In QR, various quantiles of the response variable are modeled as linear functions of the ...

Abstract: Logistic regression is a widely utilized machine learning algorithm for binary classification tasks. In this study, the logistic regression algorithm is used to classify whether a disorder ...