Nursing

Latest AI and machine learning research in nursing for healthcare professionals.

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Comparing Machine Learning and Nurse Predictions for Hospital Admissions in a Multisite Emergency Care System

Emergency department (ED) crowding strains patient care and drives up costs. Early decisions on the ...

Healthcare professionals and point-of-care innovation: changing views and emerging trends

Point-of-care technologies (POCTs) have grown increasingly prevalent in clinical and at-home setting...

Identifying Cardiogenic Shock Sub-Phenotypes with Machine Learning: A Multicenter Study Combining Clinical and Echocardiographic Data

Sub-phenotyping cardiogenic shock (CS) patients using non-traditional clustering methods represents ...

Evaluating Artificial Intelligence Assisted Nursing Education: Student Perceptions, Ethical Concerns, and Pedagogical Implications

Artificial intelligence (AI) tools are increasingly being integrated into nursing education to enhan...

Exploring Healthcare Professionals’ Perspectives on Artificial Intelligence in Palliative Care: A Qualitative Study

The use of Artificial Intelligence (AI) methods in palliative care research is increasing. Most AI p...

Early Warning Model for Patient Deterioration: A Machine Learning Approach for Nurse-Led Monitoring

The early recognition of clinical deterioration in hospital inpatients continues to be a major chall...

Large Language Models in Stroke Management: A Review of the Literature

Stroke care generates vast free-text records that slow chart review and hamper data reuse. Large lan...

Transforming Healthcare AI Education Through Micro-Learning: A Novel Partnership Model for Nursing Workforce Development

Healthcare professionals face an urgent need for AI literacy as artificial intelligence technologies...

AI vs Human Performance in Conversational Hospital-Based Neurological Diagnosis

Most evaluations of artificial intelligence (AI) in medicine rely on static, multiple-choice benchma...

Ultra-low-field MRI for imaging of severe multiple sclerosis: a case-controlled study

Severe multiple sclerosis (MS) presents challenges for clinical research due to mobility constraints...

A Better Way: Initial Acceptability Testing of Using Artificial Intelligence Tools to Accelerate Development of Trauma Clinical Guidance

Representatives of the trauma community have voiced a need for a new approach to developing clinical...

Responsible AI in Action: Planning through Implementation of a Mortality Model for Palliative Care

Interest in the use of prediction models to support referrals to palliative care is surging. Few hig...

Machine Learning Assisted Differentiation of Low Acuity Patients at Dispatch (MADLAD): A Randomized Controlled Trial

Resource Constrained Situations (RCS) at Emergency Medical Dispatch centers where there are more pat...

ChatCLIDS: Simulating Persuasive AI Dialogues to Promote Closed-Loop Insulin Adoption in Type 1 Diabetes Care

Real-world adoption of closed-loop insulin delivery systems (CLIDS) in type 1 diabetes remains low, ...

Development and Validation of a Machine Learning Model That Uses Voice to Predict Aspiration Risk

Aspiration causes or aggravates a variety of respiratory diseases. Subjective bedside evaluations of...

Benchmarking Large Language Models and Clinicians Using Locally Generated Primary Healthcare Vignettes in Kenya

Large language models (LLMs) show promise on healthcare tasks, yet most evaluations emphasize multip...

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