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

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 ...

This population-based study shows that shared and pattern-specific blood biomarkers reflect biological vulnerability ...

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

This is an important contribution that largely confirms prior evidence that word recognition - a cornerstone of development - improves across early childhood and is related to vocabulary growth. This ...

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

Explainable AI plays a central role in validating model behavior. Using established explainability techniques, the study examines which financial variables drive fraud predictions. The results show a ...

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 ...

Objectives To examine associations between The Daily Mile, a school-based active mile intervention, and pupils’ physical ...

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