Background & aim Adequate protein intake is essential during recovery from illness to prevent complications such as malnutrition, sarcopenia, and delayed wound healing. Mobile applications may support self-monitoring and early detection of inadequate intake. This study evaluated the concurrent validity …

Early identification of the palliative phase in patients with COPD and heart failure remains difficult, often delaying needed care. Since most patients are cared for at home, timely recognition in primary care is crucial. However, screening tools are rarely used, and identification relies on professional …

Achtergrond Het integreren van zorg voor (risico op) ondervoeding en sarcopenie in de eerstelijnszorg is uitdagend, omdat de beperkte fysieke nabijheid van zorgprofessionals de samenwerking bemoeilijkt. Beide aandoeningen komen veel voor bij thuiswonende ouderen en gaan gepaard met aanzienlijke achteruitgang …

The demand for assistive technology is expected to rise alongside the increasing care needs of aging populations. Ambient intelligence, particularly context awareness, offers potential benefits in addressing challenges faced by the healthcare system. In dementia care, context awareness can facilitate …

Reinforcement learning offers a promising approach for personalized, early-stage detection of behavioral events such as agitation in individuals with dementia, particularly when contextual insights from care staff are integrated. Given the scarcity and the ethical constraints of real-world agitation …

BACKGROUND: Sarcopenic obesity (SO) is a clinical condition defined by the coexistence of high body fat mass and low muscle function and mass, which increases the risk of adverse health outcomes, including disability and mortality. Early detection and frequent monitoring of SO are essential for preventive …

Family breakup dynamics in mammals can be complex due to competing interests between parents and offspring. Parents need to balance their own as well as their offspring's fitness through either terminating care early or extending care. Yet, males can disrupt this trade-off as they may force females to …

This research explored the use of deep learning to classify impact events on wind turbine blades using spectrogram images. Audio data were recorded through indoor and outdoor simulations using smartphones. The data preparation process involved converting stereo recordings to mono, applying downcasting …

The increasing prevalence of antimicrobial-resistant (AMR) bacteria in humans, animals, and the environment underscores the necessity for a rapid, sensitive, and specific method to identify resistance genes. Objectives: This study aims to develop a reliable detection tool for identifying the tetracycline-resistant …

In dit onderzoek is gekeken naar voorbeelden uit de literatuur vanuit verschillende gezondheidsdisciplines. Verschillende studies pasten machine learning (vaak deep learning) toe voor de vroegdetectie van ziekten op basis van beschikbare data uit het elektronisch patiëntendossier (EPD). Het bleek dat …