Nursing

Cultryx: Precision Diagnostic Stewardship for Blood Cultures Using Machine Learning

Background: The 2024 blood culture bottle shortage brought diagnostic resource allocation to the forefront, reflecting persistent, foundational challenges with low-value testing and empiric treatment approaches under clinical uncertainty. Objective: To determine whether a machine learning approach using electronic medical record data can predict bacteremia more effectively than existing systems an...

Development and Validation of the Intensive Documentation Index for ICU Mortality Prediction: A Temporal Validation Study

Background: Nursing documentation patterns may reflect patient acuity and clinical deterioration, yet their prognostic value remains underexplored. We developed the Intensive Documentation Index (IDI), a novel framework quantifying temporal documentation rhythms, and evaluated its ability to enhance ICU mortality prediction. Methods: We analyzed 26,153 ICU admissions of heart failure patients from...

AgentScore: Autoformulation of Deployable Clinical Scoring Systems

Modern clinical practice relies on evidence-based guidelines implemented as compact scoring systems composed of a small number of interpretable decisi...

A Unified XAI-LLM Approach for EndotrachealSuctioning Activity Recognition

Endotracheal suctioning (ES) is an invasive yet essential clinical procedure that requires a high degree of skill to minimize patient risk - particula...

Predictive Modeling of Healthcare Workers' Priorities of WHO 2030 Key Activities for Snakebite Prevention and Control in Ghana

Snakebite is a neglected public health problem that results in significant morbidity and mortality, necessitating the World Health Organization (WHO) ...

Factors affecting Artificial Intelligence usage intention among nursing students: Unified theory of acceptance and use of technology.

BACKGROUND: Nursing students' acceptance and usage of AI are crucial for embracing and implementing the technology in nursing practice in the future. ...

Empowering Healthcare Practitioners with Language Models: Structuring Speech Transcripts in Two Real-World Clinical Applications

Large language models (LLMs) such as GPT-4o and o1 have demonstrated strong performance on clinical natural language processing (NLP) tasks across m...

Empowering Healthcare Practitioners with Language Models: Structuring Speech Transcripts in Two Real-World Clinical Applications

Large language models (LLMs) such as GPT-4o and o1 have demonstrated strong performance on clinical natural language processing (NLP) tasks across m...

Beyond Black-Box AI: Interpretable Hybrid Systems for Dementia Care

The recent boom of large language models (LLMs) has re-ignited the hope that artificial intelligence (AI) systems could aid medical diagnosis. Yet d...

Integration of Virtual Technology and Artificial Intelligence Improves Satisfaction, Patient Safety, and Nursing Workforce Efficiency.

Development and Comparative Evaluation of Three Artificial Intelligence Models (NLP, LLM, JEPA) for Predicting Triage in Emergency Departments: A 7-Month Retrospective Proof-of-Concept

Triage errors, including undertriage and overtriage, are persistent challenges in emergency departments (EDs). With increasing patient influx and st...

Artificial intelligence in cardiovascular practice: Bringing the technology to the bedside.

Artificial intelligence and advanced practice nursing.

This article explores the integration of artificial intelligence (AI) in advanced practice nursing, highlighting its potential to enhance clinical dec...

Integrating artificial intelligence and machine learning in nursing practice: opportunities, methods and challenges.

[Health Equity in Mental Health Care: Challenges for Nurses and Related Preparation].

Individuals with mental illness face significant challenges in achieving health equity due to social and structural determinants, fragmented healthcar...

Perspectives and Experiences of Nurse Managers on the Impact of Artificial Intelligence on Nursing Work Environments and Managerial Processes: A Qualitative Study.

AIM: To explore the perspectives and experiences of nurse managers regarding the impact of artificial intelligence (AI) on nursing work environments a...

CRT 2025 late-breaking trials: Key takeaways.

The Cardiovascular Research Technologies (CRT) 2025 conference, a prominent gathering in the field of cardiology, convened more than three thousand at...

From Federal Policy to Bedside Care: A Canadian Perspective on Key Considerations for Nurse Executive Action for AI Adoption - A Commentary.

The integration of artificial intelligence (AI) into healthcare represents a paradigm shift with the potential to enhance patient care and streamline ...

A systematic review and sequential explanatory synthesis: Artificial intelligence in healthcare education, a case of nursing.

AIM: This review aims to explore the impact of artificial intelligence (AI) on knowledge acquisition, skills development, and attitudes among nursing ...

Postoperative self-care ability of continuous nursing based on artificial intelligence for stroke patients with neurological injury.

According to the statistics of relevant data, stroke is a relatively common cerebrovascular disease, and its incidence rate is as high as 185/100,000 ...