Nursing

Developing and Validating a Prediction Model for the Severe Pain-Fatigue-Sleep Disturbance Symptom Cluster in Patients with Lung Cancer Following Chemotherapy: A Machine Learning Analysis.

OBJECTIVES: Pain-fatigue-sleep disturbance symptom (PFS) cluster is the most common symptom cluster in patients with lung cancer following chemotherapy, which significantly impacts their quality of life. This study aims to develop and validate a machine learning-based prediction model for the severe PFS cluster and identify the relevant factors in patients with lung cancer following chemotherapy. ...

ELAI-SGCN: An explainable lightweight adaptive information-perceiving spiking graph convolutional network for EEG-based emotion recognition.

BACKGROUND: Emotion recognition is increasingly essential for diagnosing mental disorders like depression and anxiety. Electroencephalography (EEG) is widely adopted for this purpose due to its high temporal resolution and non-invasive nature. However, existing EEG-based models often neglect the brain's dynamic neural connectivity, inadequately modeling spatial topology, and rely on extensive redu...

When used for veterinary triage, artificial intelligence models recognise emergencies but are more likely than veterinary staff to flag non-urgent cases as urgent.

BACKGROUND: This study assesses the capability of ChatGPT and nurses in accurately triaging emergency patients compared to veterinarians. METHODS: Ret...

SapBark-64: A dataset of bark images for 64 fruit-tree sapling classes.

We present SapBark-64, a curated dataset of 5742 close-range bark images from 64 fruit-tree sapling classes (species/cultivar). Images were acquired i...

Nurses' ethical leadership, artificial intelligence, and moral sensitivity activation.

BackgroundWith the widespread adoption of artificial intelligence (AI) in healthcare and nursing, nurses' subjective perception of AI has become a key...

Nursing students' perceptions of gender and race in AI healthcare imagery.

BackgroundThe rapid integration of artificial intelligence (AI) into healthcare has transformed how health professionals learn, communicate, and make ...

The Role of Artificial Intelligence in Advancing Clinical Care in Cardiovascular Nursing.

Machine Learning Algorithms for Predicting Injurious Fall Risk Among Older Adults With Depression: A Prognostic Modeling Study.

BACKGROUND: Falls and related injuries (FRI) pose a large burden among older adults with depression. Proactively identifying individuals at high FRI r...

Current status and future directions for the use of artificial intelligence in pediatric critical care nephrology.

Artificial intelligence (AI) has the potential to significantly improve the practice of medicine. However, its application in pediatric critical care ...

Artificial Intelligence Technologies Supporting Nurses' Clinical Decision-Making: A Systematic Review.

BACKGROUND: The use of technology to support nurses' decision-making is increasing in response to growing healthcare demands. AI, a global trend, hold...

A curriculum framework for embedding artificial intelligence literacies in pre-registration nursing education.

BACKGROUND: Pre-registration nursing students need to be appropriately prepared for a healthcare environment that is increasingly utilising artificial...

Nursing Students' Perceptions and Attitudes on the Application of Artificial Intelligence in Nursing Education: A Mixed-Methods Systematic Review.

BACKGROUND: The utilisation of artificial intelligence in the context of nursing education has become increasingly extensive. However, various studies...

Global Research Landscape of Sleep Health in Nursing: A Bibliometric and Visualization Study.

This research intends to provide a comprehensive review of existing literature on sleep within the nursing field, employing bibliometric methods. A co...

Ultrasound to guide critical decisions: What you need to know.

BACKGROUND: Hypotension in the intensive care unit (ICU) demands rapid diagnosis and intervention, as delays in identifying the etiology of shock dire...

[Interdisciplinary, research-based teaching format for participatory technology development in nursing: a mixed methods study].

Interdisciplinary, research-based teaching format for participatory technology development in nursing: a mixed methods study Abstract: Background: Dig...

Balancing Innovation and Humanism: An Ethical Debate on AI and VR in Psychiatric Nursing Education.

BACKGROUND: Artificial intelligence (AI) and virtual reality (VR) technologies are increasingly integrated into psychiatric nursing education, present...

An explainable machine learning model for comorbidity risk stratification in patients with fractures admitted to the intensive care unit: a multicenter study.

BACKGROUND: Among traumatic-fracture patients admitted to intensive care units (ICUs), those with substantial chronic comorbidities recover more slowl...

The application of machine learning in the evaluation of urinary tract infections incidence in patients in a Nursing and Treatment Facility.

BACKGROUND: Urinary tract infection (UTI) is a serious problem in the healthcare system. It is caused by bacteria from the gastrointestinal tract. The...

Swallowing Dysfunction in Stroke: The Role of Nurses and Rehabilitation Strategies Across Recovery Phases.

BACKGROUND: Swallowing dysfunction is a common consequence of neurological disorders such as stroke, and may lead to malnutrition, aspiration, and red...

Enhancing Cultural Competence in Nursing Education Through Generative Artificial Intelligence Tools.

INTRODUCTION: Cultural competence is vital for nursing students providing patient-centered care. Generative artificial intelligence (AI) tools can enh...