Artificial Intelligence (AI) is transforming workflows across various industries, including life sciences. When deployed securely, generative AI tools can automate structured programming tasks. In clinical research, a significant challenge is converting raw trial data into the formats required for regulatory …

Context: Rapid developments and adoption of machine learning-based software solutions have enabled novel ways to tackle our societal problems. The ongoing digital transformation has led to the incorporation of these software solutions in just about every application domain. Software architecture for …

The widespread adoption of generative agents (GAs) is reshaping the healthcare landscape. Nonetheless, broad utilization is impeded by restricted access to high-quality, interoperable clinical documentation from electronic health records (EHRs) due to persistent legal, ethical, and technical barriers. …

Clinical decision support systems (CDSSs) have gained prominence in health care, aiding professionals in decision-making and improving patient outcomes. While physicians often use CDSSs for diagnosis and treatment optimization, nurses rely on these systems for tasks such as patient monitoring, prioritization, …

Background: The adoption of mobile health (mHealth) technologies among older adults remains significantly lower than in younger populations, despite their potential to promote healthier lifestyles and mitigate age-related health risks. Objective: This study aims to explore the perspectives of retirement-age …

Abstract: AI tools in radiology are revolutionising the diagnosis, evaluation, and management of patients. However, there is a major gap between the large number of developed AI tools and those translated into daily clinical practice, which can be primarily attributed to limited usefulness and trust …

Background: This study investigates patients’ use of eHealth services, their awareness of the availability of these services, and their intention to use them in primary care. It also examines patient characteristics and factors that influence the use of these services. Methods: A cross-sectional design …

AIM: The aim of this study is to measure how collaborative factors are associated with the technology readiness of nursing staff working in residential care and community nursing. The Reciprocity Instrument and Technology Readiness Index 2.0 were applied to measure this association. DESIGN: A cross-sectional …

Vroegtijdige detectie van agitatie bij mensen met dementie kan leiden tot tijdige interventies, waardoor verslechtering van de situatie wordt voorkomen en de kwaliteit van leven wordt verbeterd. De opkomst van multimodale detectie en de vooruitgang in kunstmatige intelligentie maken het haalbaar om technologie …