Latest AI and machine learning research in nursing for healthcare professionals.
BACKGROUND: Large language model tools are increasingly used in higher education, offering opportunities to support self-directed learning. In nursing education, course-specific AI virtual tutors may provide contextualised support while addressing concerns about content accuracy and alignment; yet empirical evidence remains limited. OBJECTIVE: This study evaluated the use and perceived impact of a...
Three-dimensional (3D) cancer models, notably patient-derived organoids (PDOs), address the critical limitations of traditional preclinical systems, including two-dimensional (2D) monolayer cultures and patient-derived xenografts (PDXs), by better recapitulating physiological tumor architecture and patient-specific heterogeneity, thereby revolutionizing oncology research. We chart the complementar...
BACKGROUND: Integrating artificial intelligence (AI) into healthcare is rapidly expanding, yet research on nursing students' AI literacy (AIL) remains...
BACKGROUND: Innovative behavior is crucial for enhancing clinical efficiency, promoting patient recovery, and advancing the nursing discipline. As an ...
The 21st Royan International Stem Cell Congress (3-5 September 2025, Tehran, Iran) convened the global stem cell community to assess the accelerating ...
BACKGROUND: In an attempt to overcome the space-time limitations of traditional training we used a new telemedicine home-training model (Videotraining...
There is a critical need to assess nurse educators' competencies in artificial intelligence (AI), yet no validated assessment tool currently exists to...
Artificial intelligence (AI), most often in the form of machine learning (ML), attracts high expectations across medicine and is often discussed as a ...
BACKGROUND: Artificial intelligence (AI) has rapidly transformed clinical practice by improving diagnostic accuracy and enhancing decision-making proc...
Pediatric emergency triage is a safety-critical task, and recent studies have explored whether artificial intelligence, including language models, can...
INTRODUCTION/PURPOSE: Point-of-care ultrasound (PoCUS) has evolved from bulky radiology-based machines to a core bedside tool in critical care. Traini...
BACKGROUND: Artificial intelligence (AI) is rapidly transforming healthcare practice and education, requiring students to adapt to technology-supporte...
Heart failure management in skilled nursing facilities (SNFs) is complicated by limited access to specialists, incomplete clinical documentation, and ...
INTRODUCTION: Breast cancer remains the most prevalent malignancy among women worldwide, with its pronounced molecular heterogeneity demanding therape...
Healthcare worker resilience is essential to building effective, functional, and crisis-ready health systems. This systematic map aimed to provide a c...
PURPOSE: Early detection is crucial for preventing clinical deterioration. This quality improvement project aimed to investigate the application of a ...
OBJECTIVE: Given the high alignment between deep learning and blended teaching objectives, blended teaching provides a feasible pathway for achieving ...
AIM: This study used network analysis to characterize the internal structure of artificial intelligence self-efficacy (AISE) among nursing students an...
BACKGROUND: Integrating artificial intelligence (AI) systems into nursing care often encounters obstacles stemming from unmet requirements and insuffi...