Abstract Machine learning is increasingly used in mental health research and has the
potential to advance our understanding of how to characterize, predict, and treat mental …

Abstract Background Directed acyclic graphs (DAGs) are an increasingly popular approach
for identifying confounding variables that require conditioning when estimating causal …

How to model cross-lagged relations in panel data continues to be a source of disagreement
in psychological research. While the cross-lagged panel model (CLPM) was the modeling …

Background: As atmospheric greenhouse gas concentrations continue to rise, temperature
and humidity will increase further, causing potentially dire increases in human heat stress …

Climate change is one of the greatest challenges facing humanity, and we, as machine
learning (ML) experts, may wonder how we can help. Here we describe how ML can be a …

CRISP-DM (CRoss-Industry Standard Process for Data Mining) has its origins in the second
half of the nineties and is thus about two decades old. According to many surveys and user …

Big data, high-performance computing, and (deep) machine learning are increasingly
becoming key to precision medicine—from identifying disease risks and taking preventive …

Health data are increasingly being generated at a massive scale, at various levels of
phenoty** and from different types of resources. Concurrent with recent technological …

Stroke ranks among the leading causes for morbidity and mortality worldwide. New and
continuously improving treatment options such as thrombolysis and thrombectomy have …

Misuse of statistics in medical and sports science research is common and may lead to
detrimental consequences to healthcare. Many authors, editors and peer reviewers of …