PURPOSE: This paper describes the open cohort CROSS-TRACKS, which comprises population-based data from primary care, secondary care and national registries to study patient pathways and transitions across sectors while adjusting for sociodemographic ...
BACKGROUND: Healthcare associated infections (HAI) are a major burden for the healthcare system and associated with prolonged hospital stay, increased morbidity, mortality and costs. Healthcare associated urinary tract infections (HA-UTI) accounts fo...
IMPORTANCE: Emergency medical dispatchers fail to identify approximately 25% of cases of out-of-hospital cardiac arrest (OHCA), resulting in lost opportunities to save lives by initiating cardiopulmonary resuscitation.
Studies in health technology and informatics
34755697
The demographics in Denmark are changing. People's life expectancy is increasing, which puts a strain on the home care resources. The aim of this article is to get a deeper insight to how a specific medication robot in elders' homes can be further de...
Suicide attempts are a leading cause of injury globally. Accurate prediction of suicide attempts might offer opportunities for prevention. This case-cohort study used machine learning to examine sex-specific risk profiles for suicide attempts in Dani...
Gynaecologic robot-assisted laparoscopic surgery (RALS) is adopted in all Danish regions. It is primarily used in gynaecologic oncology but is increasingly introduced in benign surgery as well. Today > 90% of Danish women with early-stage endometrial...
Scandinavian journal of surgery : SJS : official organ for the Finnish Surgical Society and the Scandinavian Surgical Society
36718674
BACKGROUND AND OBJECTIVE: Minimally invasive liver surgery is evolving worldwide, and robot-assisted liver surgery (RLS) can deliver obvious benefits for patients. However, so far no large case series have documented the learning curve for RLS.
BACKGROUND: The increasing aging population and limited health care resources have placed new demands on the healthcare sector. Reducing the number of hospitalizations has become a political priority in many countries, and special focus has been dire...
IMPORTANCE: Diagnoses and treatment of mental disorders are hampered by the current lack of objective markers needed to provide a more precise diagnosis and treatment strategy.
BACKGROUND: Machine learning (ML) models for early identification of patients at risk of hospital-acquired urinary tract infection (HA-UTI) may enable timely and targeted preventive and therapeutic strategies. However, clinicians are often challenged...