Systematic review of machine-learning models in orthopaedic trauma an overview and quality assessment of 45 studies

Aims Machine-learning (ML) prediction models in orthopaedic trauma hold great promise in assisting clinicians in various tasks, such as personalized risk stratification. However, an overview of current applications and critical appraisal to peer-reviewed guidelines is lacking. The objectives of this study are to 1) provide an overview of...

Impact of Obesity on Atrial Electrophysiological Substrate

(1) Background. Obesity is a well-established worldwide recognised risk factor for atrial fibrillation (AF). Prior review papers reported on the associations between obesity and AF development, but not on the relation between obesity and atrial electrophysiology. We therefore conducted a systematic review to describe the current knowledge of...

Digital biomarkers and algorithms for detection of atrial fibrillation using surface electrocardiograms: A systematic review: Digital Biomarkers for AF in Surface ECGs

Aims: Automated detection of atrial fibrillation (AF) in continuous rhythm registrations is essential in order to prevent complications and optimize treatment of AF. Many algorithms have been developed to detect AF in surface electrocardiograms (ECGs) during the past few years. The aim of this systematic review is to gain more insight into...

EUREC4A

The science guiding the EUREC4A campaign and its measurements is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic - eastward and southeastward of Barbados. Through its ability to characterize processes operating across a wide range of scales, EUREC4A marked a turning point in our...