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Early vascular aging and supernormal vascular aging : genetics, epigenetics, and the environment

Vascular aging (VA) is a reflection of biological aging in general and subject to many influences during the life course. It involves all aspects of the cardiovascular system but is most visible in the age-related increased arterial stiffness of large elastic arteries, such as the aorta. It is possible to measure this process by pulse wave velocity (PWV). Several studies have now documented that i

Struggling to return to everyday life—The experiences of quality of life 1 year after delirium in the intensive care unit

Background: Many critically ill patients report a change in their health-related quality of life after intensive care unit (ICU) discharge. Patients who experience delirium during their ICU stay are perceived as a fragile group of ICU survivors, and the ‘quality of life’ phenomenon needs to be studied among these patients. Aim: To explore everyday life experiences of critically ill patients with d

Data Clustering using Two-Stage Eagle Strategy Based on Slime Mould Algorithm

Data clustering is considered an important component of data mining which aims to split a given dataset into disjoint groups having the same similarities. The developed techniques for clustering have some challenges to cluster entities in complex search space and most of them aim to maximize the sum of inter-cluster distances and minimize the sum of intra-cluster distances. This objective function

Machine learning models for the prediction of polychlorinated biphenyls and asbestos materials in buildings

Hazardous materials in buildings cause project uncertainty concerning schedule and cost estimation, and hinder material recovery in renovation and demolition. The study aims to identify patterns and extent of polychlorinated biphenyls (PCBs) and asbestos materials in the Swedish building stock to assess their potential presence in pre-demolition audits. Statistics and machine learning pipelines we

Economic impact of reducing treatment gaps in depression

Background Major depressive disorder (MDD) is highly prevalent across Europe. While evidence-based treatments exist, many people with MDD have their condition undetected and/or untreated. This study aimed to assess the cost-effectiveness of reducing treatment gaps using a modeling approach. Methods A decision-tree model covering a 27-month time horizon was used. This followed a care pathway where