Nursing

Development of the nursing artificial intelligence readiness scale for nursing students: a validity and reliability study.

BACKGROUND: The rapid integration of artificial intelligence (AI) into healthcare has amplified the need for nurses who can engage with AI-supported systems safely and effectively. Assessing nursing students' AI readiness through a psychometrically sound instrument is essential for guiding curriculum design and targeted educational interventions. This study aimed to develop and psychometrically ev...

Letter to the Editor regarding "End-of-life education: An explorative study using artificial intelligence simulations in undergraduate nursing".

Recent Advances in AI for Automated ICD Coding: A Systematic Literature Review.

International Classification of Diseases (ICD) codes enable correct billing, insurance reimbursement, and healthcare analytics. However, manual coding...

Machine learning-based prediction of hospital-associated complications after tibial fracture surgery in older patients: a nationwide Japanese database study.

BACKGROUND: Older adults requiring emergency surgery for acute tibial fractures are vulnerable to hospital-associated complications (HACs), but admiss...

Teaching Critical Appraisal in the Age of Generative Artificial Intelligence: A Structured Framework for Nursing Education.

Awareness, knowledge and attitudes towards artificial intelligence among nursing students: a systematic review protocol.

INTRODUCTION: Internationally, nursing students' awareness and familiarity with artificial intelligence (AI) remain a challenge as evidenced by the cu...

Response letter to Prasetyo et al regarding "End-of-life education: An explorative study using artificial intelligence simulations in undergraduate nursing.

A Five-Step Faculty Development Checklist for Artificial Intelligence in Nursing Education.

BACKGROUND: Artificial intelligence (AI) is increasingly available to faculty and students, yet adoption remains uneven. Faculty report uncertainty ab...

Cross-national analysis of learning approaches, achievement motivation, and academic success among nursing students.

BACKGROUND: Academic success among nursing students is vital for developing the professional skills necessary to ensure the safety and quality of pati...

Artificial Intelligence and Clinician Burnout in the United States: A Narrative Review.

Burnout remains one of the defining occupational hazards of healthcare in the United States, and it spares no one on the care team: physicians, nurses...

Simulator development using natural language: clinician-led innovation through artificial intelligence.

BACKGROUND: Healthcare simulation training faces significant barriers due to the "clinician-developer gap," where educators lack programming expertise...

Effectiveness of Artificial Intelligence-Based Nursing Interventions for Chronic Illness Care: Umbrella Review.

BACKGROUND: Artificial intelligence (AI)-based nursing interventions are increasingly being used to manage chronic illnesses; however, their definitiv...

A Preliminary Approach to Fall Risk Assessment in Aged Care Facilities Using Generative AI Technologies.

Falls among elderly residents in residential aged care facilities (RACFs) are a critical public health concern, often resulting in severe injuries, re...

Non-invasive arterial blood pressure waveform generation in critically ill patients: A sensor-based deep learning approach.

Continuous monitoring of Arterial Blood Pressure (ABP) in critically ill patients requires invasive arterial catheterization, which carries risks of t...

Development and Psychometric Evaluation of the Attitudes Toward the Use of Artificial Intelligence in Nursing Care Scale.

Background and Purpose: The rapid expansion of artificial intelligence in health care is reshaping clinical workflows and decision-making, making it i...

Knowledge, attitudes, practices and ethics related to artificial intelligence among nursing students: a national cross-sectional survey in China.

BACKGROUND: Artificial intelligence (AI) is rapidly transforming healthcare. Current and future healthcare workforce, including nursing students, requ...

Predicting nurses' behavioral intention to adopt artificial intelligence in a resource-limited setting: an extended technology acceptance model study in Iran.

BACKGROUND: The integration of Artificial Intelligence (AI) into healthcare systems has the potential to substantially enhance clinical decision-makin...

From Prediction to Action: Why Bleeding Risk in Cardiac Surgery Still Eludes Us in the Era of Artificial Intelligence.

Perioperative bleeding in cardiac surgery remains common, consequential, and difficult to predict despite decades of research and expanding data avail...

Predicting Neonatal Respiratory Outcomes Using Machine Learning: A Systematic Review Through a Life Course Lens.

BACKGROUND: Neonatal respiratory outcomes remain leading drivers of neonatal intensive care unit (NICU) morbidity, mortality, and prolonged hospitaliz...

Data-driven subtypes of postoperative delirium in surgical ICU patients: a secondary analysis of a prospective cohort study.

BACKGROUND: Postoperative delirium (POD) is a heterogeneous syndrome associated with adverse outcomes. Traditional classifications may obscure underly...