Critical Care

Artificial count enhancement in lung scintigraphy for acquisition acceleration and pseudo-planar generation.

Ventilation-perfusion (V/Q) planar scintigraphy remains widely used for diagnosing pulmonary embolism (PE), despite the reported superior diagnostic performance of V/Q SPECT. In part, SPECT adoption is limited by the differences in clinical interpretation. Pseudo-planar from SPECT data can facilitate transition to SPECT, but existing methods, such as summed angular projections or forward repr...

Distinguishing common respiratory pathogens using machine learning of symptom profiles to prioritize diagnostic testing.

Clinical symptoms are critical for diagnosing and managing upper respiratory tract infections, yet systematic comparisons across common pathogens remain limited. We aimed to characterize symptom signatures across common respiratory pathogens and to develop approaches that support the prioritization of diagnostic testing across pathogens. Using a large-scale, home-based multiplex PCR testing datase...

A hypersensitive neuromorphic airflow sensor inspired by vision-compensatory scorpion mechanoreceptors for respiratory pattern analysis.

Efficient acquisition of spatial airflow information is vital for organisms to orient within complex environments and detect predators. For scorpions ...

ESCA-Net: Knowledge-Guided Encoder-Shared Classification and Auxiliary Segmentation Network for Multi-Label Catheter Malposition Assessment in Chest Radiographs.

Malpositioned medical tubes and catheters are a persistent source of iatrogenic harm in critical care, yet the radiographic interpretation burden on i...

Machine learning prediction of the change in sleepiness following continuous positive airway pressure in obstructive sleep apnea: a multi-cohort analysis.

STUDY OBJECTIVES: To predict the improvement in sleepiness following continuous positive airway pressure (CPAP) treatment for obstructive sleep apnea ...

Prediction of delayed graft function after kidney transplantation using artificial intelligence and machine learning: A Systematic Review.

INTRODUCTION: Delayed graft function (DGF) is a frequent early complication after kidney transplantation. We systematically reviewed artificial intell...

Oxygen management and targeted methods to Attack Retinopathy of Prematurity (ROP): Progress and Possibilities.

Retinopathy of prematurity (ROP) is an eye disease that severely impacts premature infants, especially those born before 31 weeks gestation and those ...

Pulmonary function estimation and reliability assessment using hybrid-optimized ensemble learning.

Objective.Pulmonary function tests are central to assessing ventilatory impairment but are often limited by accessibility, repeatability, and patient ...

Correction to "Improving Sepsis Mortality Prediction With Machine Learning Using Full Region Synthetic Sampling Approach".

[This corrects the article DOI: 10.1002/hsr2.71556.].

The Eye as a Window to Cardio-Kidney-Metabolic Disease.

The Cardiovascular-Kidney-Metabolic (CKM) syndrome reframes cardiovascular, kidney, and metabolic disease as an integrated continuum, yet its manageme...

Early Sepsis Prediction Using Interpretable Models.

Sepsis remains a major cause of morbidity and mortality in Intensive Care Units (ICUs). Timely identification of sepsis can prevent severe complicatio...

From automated ventilation to intelligent respiratory care and alarm management.

Development and validation of a comprehensive prognostic model for 28-day ICU mortality in non-traumatic subarachnoid hemorrhage: an analysis based on the MIMIC-IV database.

BACKGROUND: Due to the complex pathophysiology of non-traumatic subarachnoid hemorrhage (SAH), accurate risk prediction remains a challenge. Our aim i...

Comparative outcomes of balloon-expandable versus self-expanding transcatheter aortic valves: insights from a large-scale German registry.

BACKGROUND: While transcatheter aortic valve replacement (TAVR) has become an established alternative to surgical aortic valve replacement (SAVR), the...

Prognostication in End-Stage Kidney Disease: Tools, Evidence, and Clinical Applications.

Prognostication in end-stage kidney disease is fundamental to person-centered care and shared decision-making. This review summarizes the current evid...

Barriers and Facilitators to AI Implementation in Intensive Care Units in China: Qualitative Study Among Nurse Managers.

BACKGROUND: AI has shown significant potential in intensive care unit (ICU) nursing practice, enhancing efficiency, decision-making, and patient safet...

Value of AI in Critical Care Using Real-World Evidence on Intensive Care Unit Mortality Prediction: Cost-Utility Analysis.

BACKGROUND: AI-based models for predicting mortality have shown potential for intensive care unit (ICU) patients, but evidence regarding their cost-ef...

Multimodal Artificial Intelligence System for Risk-Adapted Cancer Survivorship Surveillance: A Multicenter Target Trial Emulation.

BACKGROUND: The growing population of cancer survivors faces immense monitoring burdens due to rigid follow-up guidelines, such as the intensive surve...

Development and validation of a deep learning model to predict heparin response in critically ill patients with deep vein thrombosis receiving continuous intravenous heparin infusion.

Continuous intravenous heparin infusion is widely used for deep vein thrombosis (DVT) in the intensive care unit (ICU), but accurate prediction of act...

A Randomized Controlled Trial Evaluating Digital Health Intervention on Phosphate Control in Patients on Dialysis.

BACKGROUND: Hyperphosphataemia is a common metabolic complication of CKD and is associated with poor health outcomes. Dietary intervention is a key st...