Latest AI and machine learning research in nursing for healthcare professionals.
OBJECTIVE: Although machine learning (ML) holds significant potential to transform healthcare, there has been a recent surge in research output that often lacks methodological rigor, contributing to a reproducibility crisis. Additionally, the growing reliance on electronic health records (EHR) for developing ML models has heightened concerns about patient data privacy. To tackle these challenges, ...
BACKGROUND: Alternative text (alt text) for images is critical for digital accessibility, but faculty often lack time or training to create it. Generative artificial intelligence (AI) offers a potential solution, although its effectiveness in education is underexplored. PURPOSE: The aim was to evaluate the quality of AI-generated alt text for course images from the perspective of nursing faculty. ...
BACKGROUND: Ischemic heart disease remains the leading cause of death worldwide. Coronary artery bypass grafting (CABG) remains the primary surgical t...
Augmented renal clearance (ARC) frequently occurs in critically ill septic patients and is known to impact survival outcomes. To address this, we aime...
Laparoscopic cholecystectomy is a high-volume procedure with relatively short operative times, leaving limited margin for further reduction in mean du...
BACKGROUND: Human Anatomy and Histology & Embryology are foundational courses in nursing education but are often challenging for students due to their...
BACKGROUND: Artificial İntelligence (AI)-assisted applications are becoming widespread in nursing practice and are creating a significant transformati...
BACKGROUND: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and confers a four to fivefold increase in ischemic stroke risk, ...
The incorporation of artificial intelligence (AI) into nursing education is becoming a key tool to respond to the growing demands for patient safety a...
BACKGROUND: Early sepsis diagnosis in children remains challenging due to nonspecific presentations. This study aimed to develop an interpretable mach...
BACKGROUND: Clinical empathy is essential for postgraduate nursing students. How it changes during clinical internships remains unclear. AIM: To explo...
Integrating generative artificial intelligence (GenAI) into nursing clinical decision-making (CDM) offers potential to bridge expertise gaps. This ran...
The increasing workload in inpatient care and the ongoing shortage of skilled workers require new approaches to demand-oriented personnel planning. A ...
This study examines how physicians and nurses in Brazil are using generative artificial intelligence tools in healthcare practice. Based on data from ...
Standardizing nursing care plan data from electronic health records is critical for interoperability and large-scale research but is often hindered by...
This study aims to analyze unstructured nursing documentation of myocardial infarction patients using clinical practice guidelines and SNOMED CT. A to...
Artificial Intelligence (AI) offers potential to support and empower nurses, yet its development depends on the availability of high-quality, standard...
This study conducted a needs assessment to evaluate contextual factors, adoption barriers, and overall readiness of municipal healthcare services to i...
As virtual nursing (VN) gains traction as a scalable solution to support hospital workflows, identifying patients best suited for VN admission assessm...
Generative AI tools hold promise for addressing global health inequities-but their potential to support scholarly productivity in resource limited set...