Latest AI and machine learning research in nursing for healthcare professionals.
BACKGROUND: Artificial intelligence (AI) is being gradually integrated into clinical nursing practice, where it plays an important role in improving nursing quality, reducing nurses' workload, and promoting the intelligent transformation of nursing. Nurses' attitudes toward AI applications in nursing directly affect the promotion and implementation of this technology. Understanding these attitudes...
BACKGROUND: Dysphagia is a common complaint that afflicts the elderly and individuals with neurological disorders. Conventional diagnostic techniques, such as Videofluoroscopic Swallowing Studies (VFSS) and Fiberoptic Endoscopic Evaluation of Swallowing (FEES), have disadvantages including inter-rater variability, radiation exposure, invasive procedures, the need for clinician observation, and sub...
Digital infrastructures such as platforms, algorithms, and artificial intelligence (AI) are rapidly reshaping the conditions under which nursing care ...
BACKGROUND: Generative artificial intelligence (GenAI) can automate time-intensive tasks and support clinical decision-making in care settings. Nurses...
Polypharmacy in post-acute and long-term care (PA/LTC) is common and is associated with falls, delirium, hospitalization, functional decline, and mort...
Emergency department (ED) triage of older adults is challenging because standard early warning scores are often insensitive to atypical presentations....
BACKGROUND: Accurate identification of patients at high risk of pulmonary infection after thoracoscopic lung cancer resection is important for timely ...
Generative artificial intelligence offers personalized patient education, yet clinical inaccuracy and lack of theoretical grounding threaten health ca...
BACKGROUND: Diabetic foot ulcers remain a leading cause of non-traumatic amputations worldwide, necessitating precise patient education and clinical m...
Preparing patients for cardiac catheterization requires critical but repetitive tasks. We conducted a prospective evaluation of the AI voice assistant...
BACKGROUND: Artificial intelligence (AI) is increasingly being integrated into healthcare systems; however, nurses' knowledge, attitudes, and perceive...
BACKGROUND: Nurse burnout is a pervasive global problem. Cognitive behavioral therapy (CBT) has been shown to reduce burnout; however, most digital CB...
BACKGROUND: This cross-sectional study investigates healthcare practitioners' perceptions of the implementation of artificial intelligence (AI) to enh...
BACKGROUND: The integration of artificial intelligence (AI) into nursing education and practice has demonstrated significant potential to enhance effi...
BACKGROUND: In intensive care unit (ICU) settings, structured team-based communication, such as multidisciplinary rounds, handoffs, and goals-of-care ...
BACKGROUND: Inequitable and time-consuming shift scheduling contributes to nurse burnout, dissatisfaction, and turnover. In Taiwan, annual nurse turno...
BACKGROUND: Ensuring accuracy and consistency in emergency department (ED) triage is vital to patient safety. Despite the presence of standardized pro...
This three-wave longitudinal study aimed to examine how medical artificial intelligence (AI) readiness impacts general well-being among nurses, focusi...
BACKGROUND: The rapid advancement of Large Language Models (LLMs) presents unprecedented opportunities for healthcare education and professional crede...
Inflammatory rheumatic diseases (IRDs) represent a significant risk factor for cerebrovascular events, independent of traditional cardiovascular risk ...