Linear regression is one of the simplest and most useful tools for analyzing data. It helps you find the relationship between variables so you can make predictions and understand patterns. In this ...

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

Health Insurance Equity, Social Determinants, Socioeconomic Status, Insurance Quality, Urban-Rural Disparity, Hukou, China ...

Michael O. Lawanson, a Nigerian data scientist at the University of Arkansas, United States, is at the forefront of global ...

The strong role of socioeconomic factors underscores the limits of purely spatial or technical solutions. While predictive models can identify where risk concentrates, addressing why it does so ...

A research team shows that phenomic prediction, which integrates full multispectral and thermal information rather than ...

Objective We performed a systematic review, meta-analysis and meta-regression to determine if dietary protein supplementation augments resistance exercise training (RET)-induced gains in muscle mass ...

Objective To characterise the age-related impact of organ damage patterns on health-related quality of life (HRQoL) in ...

By training statistical and machine-learning models to predict expert visual scores, the study demonstrates that phenomics can match or outperform ...

This study examined the relationship between the Monetary Policy Rate (MPR) and inflation across five continents from 2014 to 2023 using both Frequentist and Bayesian Linear Mixed Models (LMM). It ...

The issue: Many runners (particularly women) report that their fitness trackers tell them they’re exercising in a higher zone ...

The GC–MS dataset was integrated with the sensory data using a series of exploratory and predictive multivariate statistical ...