Latest AI and machine learning research in nursing for healthcare professionals.
BACKGROUND: Intensive Care Unit (ICU) nursing is demanding, requiring advanced clinical decision-making and emergency management skills. Simulation-based instruction is central to ICU nursing education but remains constrained by the cost and time required for scenario authoring, limited faculty capacity for feedback, and slow content updates. Large language models (LLMs)-based pedagogical agents m...
BACKGROUND: Rousing Generation Z's (Gen Z) interest in historical nursing theorists presents a challenge for nurse educators. An innovative method for engaging Gen Z with historical figures in nursing involves the use of artificial intelligence. METHOD: Undergraduate nursing students were assigned a historical nursing theorist to interview using ChatGPT (OpenAI). To start a historical conversation...
The concept of integrating hemodynamic variables to define specific profiles or phenotypes has been established for decades. Describing hemodynamic ph...
AIM: To offer a student-focused critical evaluation of the content and use of a digital competencies discipline-specific toolkit that was co-designed ...
BACKGROUND: The prevalence of malnutrition is common in hospitalized patients. Timely and efficient nutrition support can improve clinical outcomes an...
AIM: To examine the perinatal experiences of at-risk mothers and their engagement with mobile-health-based care. DESIGN: A qualitative descriptive stu...
AIMS: The study focused on nurses' familiarity with, beliefs about, and attitudes towards artificial intelligence, aiming to identify configurations o...
AIM: To systematically map evidence on the application of AI systems in nursing workforce management, with a targeted focus on the role of nurse leade...
AIM: Healthcare systems face a growing challenge: as technology advances, patients increasingly feel like data points in systems that prioritise effic...
BACKGROUND AND AIMS: Autonomous mobile robots (AMRs) have an increasingly wide range of medical applications. However, their use in endoscopy centers ...
BACKGROUND: Timely detection and monitoring of abdominal aortic aneurysms (AAAs) are necessary to prevent ruptures and decrease mortality. Artificial ...
AIMS: To predict nurses' turnover intention using machine learning techniques and identify the most influential psychosocial, organisational and demog...
The rapid integration of artificial intelligence in healthcare, accelerated by the Trump administration's 2025 AI Action Plan and private sector innov...
Carpal tunnel syndrome (CTS) is recognized as the most frequently encountered median nerve (MN) entrapment neuropathy, with a disproportionate burden ...
AIM: To determine the perceptions and readiness of nurses regarding the integration of artificial intelligence (AI) into healthcare services. DESIGN: ...
AIM: This study aimed to validate the mediating role of nurses' AI trust in the relationship between AI uncertainties and AI competence. DESIGN: A cro...
AIMS: To (1) analyse managers' experiences with handling patient safety incident reports in an incident reporting software, identifying key challenges...
AIMS AND OBJECTIVES: To assess the knowledge and opinions of operating room nurses about artificial intelligence. BACKGROUND: Artificial intelligence ...
Septic shock remains one of the most severe complications of infection, defined by circulatory, cellular, and metabolic dysfunction and associated wit...
This study explored nurses' perspectives on the adoption and utilization of artificial intelligence (AI) in clinical practice within a large universit...