Critical Care

Deep Learning-Based Reconstruction Improves Image Quality in Canine Cranial Abdominal MRI: A Prospective Pilot Study.

The application of deep learning-based reconstruction (DLR) to magnetic resonance imaging (MRI) has been recently introduced in human and veterinary medicine to improve image quality without prolonging acquisition time. We hypothesized that cranial abdominal MRI with DLR would have superior image quality than conventional MRI. This prospective comparative pilot study aimed to compare cranial abdom...

From Triage to Intensive Care: A Qualitative Study of Nurses' Experiences with AI-Enabled Decision Support.

BACKGROUND: Artificial intelligence (AI)-enabled decision support systems are increasingly used in emergency departments and intensive care units to support triage, prediction of deterioration, sepsis recognition and escalation decisions. Although these tools may enhance patient safety, they also introduce new challenges for nurses who remain professionally accountable for clinical judgement in hi...

Blinded, bias-controlled multi-rater evaluation of human-versus-AI brain metastasis segmentation using a hybrid foundation-model framework.

BACKGROUND: Accurate segmentation of brain metastases (BM) is essential for diagnosis, stereotactic radiosurgery planning, and longitudinal assessment...

Prognostic significance of the endothelial activation and stress index in acute respiratory distress syndrome: a retrospective cohort study.

Endothelial cells play a crucial role in the pathogenesis of acute respiratory distress syndrome (ARDS). The Endothelial Activation and Stress Index (...

Machine learning-based prediction of ICU admission and mortality in Crimean-Congo hemorrhagic fever by using wide-range targeted metabolomics.

PURPOSE: This study aimed to evaluate the potential of amino-acid profiles to predict disease progression in patients with Crimean-Congo Hemorrhagic F...

Comparative machine learning approaches to prognosticate clinical outcomes in oral and maxillofacial space infections: a retrospective analysis.

BACKGROUND: The objective of this study was to evaluate the performance of multiple machine learning algorithms to provide evidence supporting early i...

Artificial intelligence for environmental sustainability across sectors: a scoping review and evidence map for nursing and health policy.

BACKGROUND: Health systems are expected to reduce environmental impacts while preserving safe, continuous and equitable care. Artificial intelligence ...

Risk prediction of sepsis-associated acute kidney injury: development, validation of a machine learning model with multicenter data.

BACKGROUND: Sepsis-associated acute kidney injury (SA-AKI) is a common and severe complication in intensive care unit (ICU) patients, with high incide...

Synergistic Geroprotectors Mapping through Systems Machine Learning and Graph Neural Networks.

Geroscience offers a transformative paradigm by targeting shared aging hallmarks to enable simultaneous modulation of multiple age-related disorders (...

The HLH-Risk-Calculator is a machine learning-based tool to predict course & mortality of secondary hemophagocytic lymphohistiocytosis.

PURPOSE: Secondary hemophagocytic lymphohistiocytosis (sHLH) is a life-threatening hyperinflammatory condition. While few diagnostic scores are establ...

From companion technologies to social care infrastructure: A multi-level perspective on loneliness-related support in dementia care in an era of artificial intelligence (AI).

Loneliness and social isolation are important psychosocial concerns in dementia care, but they are difficult to address through pharmacological treatm...

Artificial intelligence (AI)-based pose estimation detects movements linked to unplanned tube removal in ICU patients.

Unplanned removal of life-sustaining tubes in intensive care units (ICUs) poses serious risks, yet existing monitoring methods relying on physical res...

Postoperative cerebral infarction after major thoracic and abdominopelvic surgery: a retrospective single-centre cohort study of incidence, risk factors, and outcomes.

BACKGROUND: Postoperative cerebral infarction (POCI) is an uncommon but potentially fatal complication of major non-cardiac surgery and is associated ...

Machine learning-based cross-sectional exploration of depression-chronic pain associations in chronic respiratory disease patients.

BACKGROUND: Chronic respiratory diseases (CRD) are a leading global cause of death, with high comorbidity rates of depression and chronic pain forming...

Integrating Machine Learning and Pharmacology Reveals NF-κB-Mediated Inflammatory Regulation by Shuanghuanglian Injection in Acute Lung Injury.

ETHNOPHARMACOLOGICAL RELEVANCE: Shuanghuanglian Injection (SHLI) is a traditional Chinese medicine formulation derived from Lonicerae Japonicae Flos, ...

Predictive Model for Thrombosis in Mature Autologous Arteriovenous Fistula.

OBJECTIVE: Based on the "high-risk stenosis-thrombosis" theory, this study developed a risk prediction model for thrombosis in mature autogenous arter...

Deep learning for time-series segmentation of mechanical ventilator waveforms.

Accurate segmentation of ventilator waveforms is essential for detecting patient-ventilator asynchronies (PVAs), yet current heuristic methods can fai...

Orchestrator multi-agent clinical decision support system for secondary headache diagnosis in primary care.

OBJECTIVE: Secondary headaches require urgent recognition due to potentially devastating consequences if untreated. Despite established clinical "red ...

Identifying subgroups of ICU patients with high mortality rates using machine learning: A nationwide, population-based study.

PURPOSE: Identifying subgroups of intensive care unit (ICU) patients with high mortality rates can provide directions in policy making about appropria...

Artificial intelligence-enhanced nurse navigation for monitoring and care of long COVID.

INTRODUCTION: Long COVID is a multisystem condition with challenging diagnosis. Nurse-navigation, a patient-centered intervention, can enhance educati...