The US government has reopened following its longest-ever shutdown, setting the stage for the eventual release of the gold-standard federal data that is crucial in analyzing the health and trajectory ...

An emerging approach in AI innovation is hybrid AI, which combines the scalability of machine learning (ML) with the ...

Introduction Burnout and reduced well-being are highly prevalent among Japanese medical students during clinical training. Scalable, evidence-based interventions are urgently needed. This protocol ...

Background Adverse childhood experiences (ACEs) are linked to poor health and social outcomes, with growing interest in their ...

Two weeks before the U.S. Federal Reserve's last meeting, with the federal government's data spigot closed, Atlanta Fed staff ...

Statistics on private sector jobs from ADP and BLS are highly correlated. Since the start of ADP’s series in 2010, the R 2 for the two national private sector employment reports is 0.9817 (when ...

Background Although voting is recognised as a social determinant of health, the association between electoral participation ...

Thanks to AI, data science tasks that once demanded specialized skills can now be performed faster, more accurately and at a ...

This study presents a valuable finding on mutations in ZNF217, ZNF703, and ZNF750 through 23 breast cancer samples alongside matched normal tissues in Kenyan breast cancer patients. The evidence ...

I 'm a big fan of Python for data analysis, but even I get curious about what else is available. R has long been the go-to language for statistics, but the "Tidyverse" has given the language a serious ...

Turn information overload into actionable insight and gain understanding of the macroeconomic elements driving market actions.

Abstract: This study aims to evaluate the innovation system of the metropolitan statistical areas (MSAs) in the USA through the application of a two-stage data envelopment analysis model. Our ...