Nursing

Validity and Reliability of the Medical Artificial Intelligence Readiness Scale, Korean Version: A Methodological and Cross-Sectional Study.

This study aimed to translate and culturally adapt the Medical Artificial Intelligence Readiness Sca...

Harnessing Artificial Intelligence to Strengthen Acute and Critical Care Nursing Practice: A Systematic Review.

BACKGROUND: Artificial intelligence (AI) is reshaping clinical decision support systems (CDSSs). In ...

Trusting the Algorithm or Trusting the Nurse? Critical Care Nurses' Experiences of Automation Bias and Professional Autonomy in AI-Assisted Early Warning.

BACKGROUND: Artificial intelligence-assisted early warning systems (AI-EWS) are increasingly integra...

Shadow Artificial Intelligence in Intensive Care Nursing: Why Informal Use Requires Governance.

The Role of Machine Learning and Artificial Intelligence in Enhancing Critical Care Nursing Practice: A Scoping Review.

BACKGROUND: Artificial intelligence (AI) and machine learning (ML) are emerging as transformative to...

Leveraging Artificial Intelligence to Improve Perioperative Staffing Consistency: A Quality Improvement Initiative at a Large Academic Medical Center.

A large academic medical center in the Pacific Northwest addressed perioperative staffing challenges...

Evaluating the Accuracy, Empathy, and Readability of Generative AI Versus Registered Nurses in Discharge Planning: A Vignette-Based Study.

AIM: To compare the multidimensional performance of discharge instructions generated by generative A...

Multisite Implementation of a Digital Wound Model of Care: A Post-Implementation Multimethods Evaluation of Patient and Clinician Perspectives and Lessons Learned.

This study evaluated district-wide implementation of a digital wound model of care combining an arti...

Exploratory Analysis of Electrical Impedance Tomography Features Associated with Spirometric Airflow Limitation.

Introduction: Electrical impedance tomography (EIT) is a noninvasive, radiation-free imaging modalit...

Artificial intelligence in emergency medicine: from algorithmic performance to real-world clinical integration - understanding the implementation gap.

BACKGROUND: Emergency departments (EDs) operate under time pressure, diagnostic uncertainty, and cog...

The diagnostic accuracy of left ventricular ejection fraction assessment between visual and artificial intelligence-based algorithms on bedside ultrasound.

BACKGROUND: Focused cardiac ultrasound (FoCUS) has become the standard of care for bedside assessmen...

Artificial Intelligence in Mental Health Nursing: A Bibliometric Analysis of Research Trends, Knowledge Structures and Emerging Themes.

INTRODUCTION: Artificial intelligence technologies are increasingly transforming mental healthcare t...

Machine Learning-Driven Risk Clusters for Adverse Outcomes in Patients Hospitalized with Acute Heart Failure: Using a Retrospective Cohort Data.

AIM: Heart failure (HF) poses a growing public health burden, yet conventional risk stratification m...

Guiding Doctoral Students in the Appropriate and Ethical Use of Artificial Intelligence for the Doctor of Nursing Practice Proposal Development.

Background: Developing a Doctor of Nursing Practice (DNP) project proposal is challenging as student...

Turkish Adaptation of the Nursing Students' Fear Toward Artificial Intelligence Scale: A Study of Validity and Reliability.

Background and Purpose: Most nursing students report having limited knowledge about artificial intel...

The LoVe score: Development and validation of a bedside clinical index to identify patients at risk for prolonged invasive mechanical ventilation.

BACKGROUND: Early management decisions after intubation, such as humidification strategy or initiati...

Enhancing the accuracy of bioimpedance-derived appendicular skeletal muscle mass in aged adults through machine learning.

PURPOSE: Appendicular Skeletal Muscle Mass (ASMM) estimation via Bioelectrical Impedance Analysis (B...

Development of a machine learning prediction model for overactive bladder in female nurses: the NURS study.

PURPOSE: To develop and internally validate interpretable machine-learning models for identifying in...

Non-inferiority analysis of a fetal heart rate artificial intelligence algorithm to registered nurse assessment.

INTRODUCTION: Cardiotocography (CTG) is widely used for monitoring fetal heart rate (FHR) and uterin...

Embodied AI in the operating room: a voice-interactive robotic scrub nurse for surgical instrument handoffs.

Embodied artificial intelligence may extend surgical robotics beyond teleoperation by enabling robot...

Avoiding the "Desert of the Real": Preserving Evidence-Based Nursing in the Age of AI.

AIM: A discussion of the implications of generative artificial intelligence (AI) evidence synthesis ...