Nursing

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

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Pre-AF 13: An Interpretable Atrial Fibrillation Risk Score Mined from Discharge Reports

Background. Atrial fibrillation (AF) is the most prevalent cardiac arrhythmia and a major determinant of prognosis. Established AF risk scores rely on factors (older age, hypertension) nearly ubiquitous among patients with cardiovascular disease (CVD), offering limited stratification in this high-risk group. Most target long-term (5-10 year) rather than medium-term prediction. We developed interpr...

Jun 9 2026 2606.10725v1

Performance evaluation and benchmarking across 16 large language models on a comprehensive real-world emergency department triage data set

Background Emergency department (ED) triage is a high-stakes clinical decision process that determines patient prioritization and resource allocation under time pressure. Large language models (LLMs) have recently been proposed as decision-support tools for triage, yet most evaluations rely on simulated scenarios or curated datasets. Evidence from real-world clinical environments remains limited. ...

A Hierarchical Visual EEG Framework for the Assessment of Disorders of Consciousness

The objective assessment of patients with disorders of consciousness (DOC) remains a significant clinical challenge. Behavioral scales like the Coma R...

Compute-Optimal Network Design for Echocardiography Myocardial Segmentation and Perfusion Quantification using Neural Scaling Laws

Myocardial perfusion quantification using contrast-enhanced ultrasound offers a bedside non-ionizing alternative to nuclear imaging modalities. Howeve...

Jun 4 2026 2606.06725v1
Development and validation of a dynamic risk stratification tool for predicting multidrug-resistant bacterial infections in ICU patients: A clinical prediction model and web-based calculator

Background: Multi-drug resistant Bacterial (MDRB) Infections in the intensive care units (ICUs) substantially elevate patient mortality, prolong hospi...

JMed48k: A Multi-Profession Japanese Medical Licensing Benchmark for Vision-Language Model Evaluation

We introduce JMed48k, a multi-profession Japanese healthcare licensing benchmark for evaluating vision-language models. Built from official PDF materi...

May 21 2026 2605.22080v1
SepsisAI Orchestrator: A Containerized and Scalable Platform for Deploying AI Models and Real-Time Monitoring in Early Sepsis Detection

Despite strong predictive results in the clinical machine learning literature, the translation of these models into bedside use remains limited by sys...

May 21 2026 2605.22331v1
Interpretable Predictive Modeling for Medical Data Using Boolean Rule-aware Regression

Purpose: In clinical practice, accurate prediction of disease risk must be accompanied by transparent, human-understandable explanations to support di...

Contactless ultrasound chest vibration mapping discriminates respiratory and cardiac patients from healthy individuals.

Contactless assessment of cardiopulmonary function remains an unmet need, with current approaches relying either on subjective clinical examination or...

Modifying integrated nursery management through the lens of mycorrhizal ecology improves radiata pine seedling performance and reshapes root mycobiome structure at operational industry scale

Early management decisions in operational forestry are critical for plantation success because it strongly influences seedling quality at planting. Be...

Solving Emergency Department Triage with Small Language Models

Emergency department (ED) triage assigns patients a five-level Emergency Severity Index (ESI) score that determines care priority. We investigate the ...

Self-Care Competence and AI-Supported Learning as Predictors of Enhanced Clinical Decision-Making Skills Among Nurses

Clinical decision-making is a critical competency for nurses particularly in resource-constrained healthcare systems where frontline practitioners mus...

Non-Invasive Arterial Blood Pressure Waveform Generation in Critically Ill Patients: A Sensor-Based Deep Learning Approach

Continuous monitoring of Arterial Blood Pressure (ABP) in critically ill patients requires invasive arterial catheterization, which carries risks of t...

No One Left Behind: Adaptive Tablet Modalities for Digitally Excluded Emergency Department Patients Design, Implementation, and Social Evidence for an Impairment-First Interface

Background: The urgent care departments in Europe face a structural paradox: accelerating digitalisation is accompanied by a patient population that i...

Combining Token Classification With Large Language Model Revision for Age-Friendly 4M Entity Recognition From Nursing Home Text Messages: Development and Evaluation Study

Background: Secure text messages (TMs) exchanged among interdisciplinary care teams in nursing homes (NHs) contain clinical information that aligns wi...

Human-supervised, large language model-based clinical decision support aligned to national newborn protocols in Kenya: a pragmatic, early-stage evaluation

Introduction: Timely, protocol-adherent clinical decisions are crucial for reducing neonatal mortality in low-resource settings. Translating extensive...

Trust in, acceptance of, and responsibility for, artificial intelligence in healthcare: patient and healthcare practitioner considerations

Objectives Using qualitative methods, this study aimed to provide a comparative overview of the similarities and differences in perspectives towards A...

Scalable Micro-Credentials for AI Literacy in Healthcare: An AI-Assisted Framework for Expert-Led Education

The rapid evolution of clinical guidelines and artificial intelligence has created a velocity gap in medical education, where traditional curricula fr...

Ensuring Safety in Automated Mechanical Ventilation through Offline Reinforcement Learning and Digital Twin Verification

Mechanical ventilation (MV) is a life-saving intervention for patients with acute respiratory failure (ARF) in the ICU. However, inappropriate ventila...

Mar 11 2026 2603.11372v1
Layer-wise Instance Binding for Regional and Occlusion Control in Text-to-Image Diffusion Transformers

Region-instructed layout control in text-to-image generation is highly practical, yet existing methods suffer from limitations: (i) training-based app...

Mar 6 2026 2603.05769v1
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