Critical Care

SMART: spatial multi-omic aggregation using graph neural networks and metric learning.

Spatial multi-omics enables the exploration of tissue microenvironments and heterogeneity from the perspective of different omics modalities across distinct spatial domains within tissues. To jointly analyze the spatial multi-omics data, computational methods are desired to integrate multiple omics with spatial information into a unified space. Here, we present SMART (Spatial Multi-omic Aggregatio...

Proteomic profiling and pathway analyses reveal molecular signatures and immune networks in pediatric sepsis.

BACKGROUND: Sepsis remains a leading cause of childhood mortality worldwide. Most deaths occur within the first few days of presentation, underscoring the urgent need for early recognition and biologically informed treatment strategies. The heterogeneous etiology of sepsis involves complex, intertwined biological networks, explaining why single-biomarker approaches have proven inadequate for captu...

Integrating metabolomics and machine learning with in silico analysis to identify early biomarkers and molecular interactions in sepsis-associated acute kidney injury.

Benchmarking Hybrid CNN-Transformer Versus Pure Transformer Architectures for Accelerated Hyperpolarized 129Xe MRI Reconstruction.

BACKGROUND: Hyperpolarized 129Xe MRI faces technical challenges including low signal-to-noise ratio and breath-hold constraints. Current literature fo...

Combined use of serum KL-6 and respiratory functional parameters for identifying fibrotic lung damage in SARS-CoV-2-induced interstitial pneumonia.

BACKGROUND: Post-COVID19 pulmonary fibrosis (PCPF) has been reported in a significant proportion of patients who survive the acute SARS-CoV-2 infectio...

Natural Language Processing Methods Automate Molecular Marker Extraction From Glioma Pathology Reports.

BACKGROUND AND OBJECTIVES: Molecular markers such as isocitrate dehydrogenase (IDH) and alpha-thalassemia/mental retardation syndrome X-linked (ATRX) ...

AI-derived left-to-right cardiac chamber volume ratios in coronary artery calcium scans strongly predict heart failure.

AIMS: The AI-CVD initiative seeks to extract actionable insights from coronary artery calcium (CAC) scans beyond the traditional CAC score. We previou...

At the Edge of Chaos: Complexity Science and Critical Care in the Era of Artificial Intelligence.

Critical care unfolds at the crossroads of highly complex, nonlinear systems. The intersection of pathophysiology, human behavior, and clinical operat...

Machine learning predicts sepsis deterioration trajectories.

Sepsis has heterogeneous clinical trajectories, but conventional severity scores offer only static risk estimates. Timely, dynamic prediction could en...

Characterizing heterogeneity and subphenotyping acute respiratory distress syndrome with computed tomography.

Acute respiratory distress syndrome (ARDS) is a heterogeneous clinical syndrome rather than a single disease. Patients who meet the same diagnostic cr...

Computational Discovery of MERS-CoV Main Protease Inhibitors Through Screening and Molecular Dynamics Simulations.

Targeting the main protease (Mpro) of coronaviruses has emerged as a promising therapeutic strategy for combating viral infections. Despite the global...

Subtypes estimation in single-cell multi-omics data via S-multi-SNE.

Single-cell RNA sequencing (scRNA-seq) has rapidly become an essential method in modern biology, as it allows global characterisation of transcriptomi...

Nonlinear dynamical analysis of chaos, fractal complexity, and entropy in EEG signals during music therapy in ICU burn patients.

Music therapy (MT) is known to influence brain dynamics; however, its effects on nonlinear electroencephalogram (EEG) characteristics in clinical sett...

Toward a multi-level, needs-based approach to cancer navigation: Considerations for service design.

Evidence suggests that patient navigation can help address ongoing barriers to accessing timely, appropriate, and quality cancer care. It also support...

A Multi-Scale Hybrid Efficient Deep Learning Model for COPD Detection Using Respiratory Sounds.

Chronic obstructive pulmonary disease (COPD) is a prevalent respiratory disease, and early diagnosis is crucial for timely intervention and improved p...

International Delphi consensus on acute kidney injury: Foundations for AI-driven digital twin development in critical care nephrology.

BACKGROUND: Acute kidney injury (AKI) in critically ill patients is clinically complex and heterogeneous, limiting the development of structured simul...

Operational building datasets from multipurpose buildings in Denmark and Switzerland: High-resolution energy use and room measurements.

The dataset comprises Building Management System (BMS) data from an educational building located on the main campus of Aalborg University in Denmark, ...

A cost-sensitive multiclass machine learning framework for postoperative neurosurgical triage (Neuro-TACTIC).

Postoperative placement of patients into a regular ward, an intermediate-care unit (IMC), or an intensive care unit (ICU) is critical for balancing pa...

Integrated analysis of the gut mycobiota and plasma metabolome reveals mortality and age-specific characteristics in sepsis.

Letter to the Editor: "Evaluating the efficacy of large language models in predicting intensive care unit admission needs".

This letter comments on the study by Turan et al., which evaluates the efficacy of large language models (LLMs) in predicting ICU admission needs. Whi...