Nursing

Predicting Intramyocardial Hemorrhage Before Reperfusion in STEMI Patients With Intrinsically Explainable Artificial Intelligence.

BACKGROUND: Intramyocardial hemorrhage (IMH) complicates approximately 40% of reperfused ST-segment elevation myocardial infarctions (STEMIs) and is associated with worse outcomes. No method identifies patients at risk before reperfusion. OBJECTIVES: The objective of the study was to develop and evaluate an explainable artificial intelligence approach for pre-reperfusion IMH prediction and transla...

Disparities in Engagement with an Artificial Intelligence-Based Chat Intervention Post-appendectomy.

PURPOSE: Artificial intelligence (AI)-based text messaging, or "chat," in post-appendectomy care has been shown to decrease preventable emergency department visits. As digital health grows, it is important to assess the impact of technology-based interventions across patients with diverse backgrounds and socioeconomic risk factors. The purpose of this study was to evaluate engagement with an AI-ba...

Re: "A Dynamic Machine Learning Approach to Complement Nurse-Led Clinics in Identifying High-Risk Patients with Intermittent Claudication".

Multimodal assessment of minimally conscious state and cognitive motor dissociation in neurocritical care: A critical review.

Minimally conscious state (MCS) is characterized by inconsistent but clearly discernible clinical and behavioral evidence of consciousness. Cognitive ...

Predicting kinesiophobia in knee osteoarthritis: a head-to-head comparison between machine learning and traditional regression models.

BACKGROUND: Although machine learning (ML) holds promise for improving clinical identification, its application to kinesiophobia in knee osteoarthriti...

Profiles of artificial intelligence literacy and associations with evidence-based practice competence among nurses: a latent profile analysis.

AIMS: To understand the current state of nurses' artificial intelligence (AI) literacy. This study employs latent profile analysis to examine the rela...

Artificial intelligence literacy and influencing factors among clinical nurses in southeastern China: a latent profile analysis.

BACKGROUND: The rapid integration of artificial intelligence (AI) in clinical settings presents unprecedented opportunities, yet it concurrently trigg...

Measuring Return on Investment for Professional Development Activities: 2026 Known Cost of Outcomes Table and Generative AI Implications.

Over the past decade, nursing professional development practitioners (NPDPs) have advanced efforts to measure the economic impact of educational activ...

Accuracy of Machine Learning to Predict Upper-Limb Outcome Within the First 72 Hours Poststroke.

BACKGROUND: Timely and accurate prediction of poststroke motor outcome is important for efficient rehabilitation planning and resource allocation. Exi...

Artificial Intelligence Applications Versus Manual Methods For Literature Retrieval: A Comparative Analysis.

BACKGROUND: Artificial intelligence (AI), particularly generative and large language models, is being used in nursing education, practice, and scholar...

Caregiver Preferences for AI-Supported Telemedicine in Pediatric Palliative Care: A Discrete Choice Experiment.

BackgroundAsynchronous telemedicine may support home-based pediatric palliative care (PPC) by improving access to professional guidance and reducing c...

Comparison of the performance of ChatGPT Plus, Gemini Pro, and experienced nurses in pediatric emergency triage using physician reference assessment: A prospective observational study.

AIM: We aimed to evaluate the performance of ChatGPT Plus and Gemini Pro, two large language model-based artificial intelligence (AI) tools, to predic...

Generative artificial intelligence in nursing care research: Applications across the research process.

Generative artificial intelligence has undergone rapid development in recent years, and its integration into health research is transforming the ways ...

Psychological safety and perceived risk are associated with emergency nurses' intention to use AI-augmented triage systems.

Emergency department overcrowding places sustained pressure on triage workflows and patient prioritization. Artificial intelligence (AI)-augmented tri...

Building a predictive model for nursing students' use of artificial intelligence: advancing technology acceptance and application in nursing education.

BACKGROUND: With the rapid development of artificial intelligence (AI) technology, its application across various industries, particularly in healthca...

HeLP-BAG score: a novel data-driven scoring system for predicting post-operative 30-day mortality using 24-hour preoperative data.

BACKGROUND: Accurate preoperative risk stratification remains challenging, as existing scoring systems are often complex, invasive, or limited to spec...

Exploratory Evaluation of Dual Digital Platforms for Acute Brain Conditions in Medically Underserved Rural Areas : A Chuncheon, Gangwon-do Experience.

OBJECTIVE: To describe an exploratory initial experience with two complementary digital platforms consisting of an AI-based telemedicine system and an...

Generative Artificial Intelligence Chatbots for Parental Guidance in Pediatric Orthopaedics: A Pilot Feasibility Study.

BACKGROUND: Parents of children with pediatric orthopaedic conditions frequently have questions after their clinic visit, and a reliable postconsultat...

Utilization of Heritage Manifestations in a Reminiscence Programme (App) Directed at Older Adults with and Without Neurocognitive Disorder, Employing AI: A Pilot Study in Portugal and Spain.

Cultural and intangible heritage has been part of human daily life since time immemorial, fulfils a function within the community and acts as an eleme...

Usability of an Artificial Intelligence-Enhanced Multispectral Imaging Tool for Burn Assessment: A Multi-Centre Retrospective Heuristic Evaluation.

Accurate burn depth assessment remains difficult. AI-enhanced multispectral imaging (AI-MSI) offers objective, image-based predictions, but evidence o...