Critical Care

A Histone Deacetylase Activity Model for the Discovery and Validation of Sepsis Biomarkers.

INTRODUCTION: Histone deacetylases (HDACs) play critical roles in immune regulation and inflammatory responses in sepsis. This study identified HDAC-related genes and explored their potential roles in sepsis. MATERIALS AND METHODS: HDAC scores were computed by ssGSEA. WGCNA was applied to identify HDAC-related gene modules, followed by functional enrichment analysis. Machine learning methods were ...

Predicting public Intensive care unit mortality and hospitalization using Data: An evaluation of Brazil's Largest COVID-19 epidemiological dataset.

OBJECTIVES: To assess the SRAG dataset's potential for modeling COVID-19 mortality and LOS-ICU, identify key data gaps, and support the development of predictive tools for ICU planning in future outbreaks. METHODS: The SRAG dataset was split into training and test sets, followed by a hybrid feature variable selection strategy, which applied the XGBoost classifier and subsequent inclusion of comorb...

Artificial intelligence-based detection of acute postoperative airway complications following anterior cervical spine surgery: a retrospective imaging evaluation.

STUDY DESIGN: Retrospective imaging evaluation using an artificial intelligence (AI)-generated model. PURPOSE: To develop novel AI software for early ...

Novel deep learning-based optimization framework for the classification of respiratory diseases using lung sound analysis.

Respiratory disease classification using lung sound analysis offers a non-invasive and cost-effective diagnostic alternative to traditional imaging-ba...

Clinical decision support system for breathlessness.

PURPOSE OF REVIEW: This review summarizes high-level evidence on clinical decision support systems, both more classical rules-based and emerging artif...

MoSA-Det: motion state adaptive object detection for sports videos.

Object detection in sports videos serves as a fundamental task for applications such as intelligent broadcasting, tactical analysis, and athlete track...

Artificial intelligence-driven cluster analysis for identifying clinical phenotypes in suspected sepsis patients in the emergency department.

Building your future ICU in Asia Pacific: A structured regional priority-mapping summit report from the Asia Pacific Critical Care Societies Summit 2025.

OBJECTIVE: To summarise the proceedings of the third Asia Pacific Critical Care Societies Summit and identify regionally aligned priorities for the "F...

Exploratory prediction model for deep vein thrombosis in intensive care patients after anticoagulation therapy: An observational study.

BACKGROUND: Despite low-molecular-weight heparin (LMWH) prophylaxis, the incidence of deep vein thrombosis (DVT) remains high in intensive care unit (...

SELFormer-guided discovery of xanthohumol and cirsilineol as multi-target natural therapeutics for type 2 diabetes: computational prediction and experimental validation.

Type 2 diabetes mellitus (T2DM) requires multi-target therapeutic approaches addressing both insulin resistance and insulin secretion deficits. Althou...

Diagnostic assessment of artificial intelligence reconstruction on accelerated prostate MRI: a retrospective, paired, multi-reader multi-case study.

OBJECTIVES: To determine whether AI-reconstructed prostate MRI at reduced acquisition times maintains prostate cancer (PCa) detection performance comp...

Enhancing lung diseases recognition through CNN-RNN methodologies.

Diagnostics of respiratory disorders greatly benefit from medical imaging, especially X-ray imaging, which offers important information about the anat...

A machine learning model for post-operative sepsis prediction in acute surgical patients: a multi-centre, prospective study.

Parsimonious and explainable biomarker-based severity score for hospitalised patients with COVID-19-related respiratory infections: development, validation and XAI benchmarking.

BACKGROUND: Severity scoring systems are increasingly important tools for stratifying hospitalised patients, guiding treatment decisions, and enabling...

Detection of Interstitial Lung Abnormalities on Chest Radiographs: Diagnostic Performance of Radiologists and Artificial Intelligence.

Background: Interstitial lung abnormalities (ILA) on chest CT are receiving growing attention given their association with progression to interstitial...

Performance of Large Language Models vs Conventional Machine Learning for Predicting Clinical Outcomes With Limited Data: Comparative Study.

BACKGROUND: Machine learning (ML) can be used to predict clinical outcomes. Training predictive models typically requires data for hundreds or thousan...

Patient-Specific Cardio-Respiratory Model for Optimization of Cardiac Radioablation.

Stereotactic Arrhythmia Radioablation (STAR) is a promising treatment for refractory ventricular tachycardia. However, its precision may be hampered b...

Explainable Prediction of ICU Transfer in Acute Pancreatitis: A Neural Network Model With SHAP Interpretability for Clinical Decision Support.

OBJECTIVE: Acute pancreatitis (AP) is a life-threatening disorder commonly observed in emergency departments. Patients with acute pancreatitis may nec...

Robust Semi-Supervised Feature Selection With Multi-Granularity Zentropy Modeling.

High-dimensional and weakly supervised (HiDWS) data present significant challenges for traditional machine learning and pattern recognition. Although ...

Bulk Microarray and Single-Cell Transcriptomic Analyses Reveal Bacterial Lipopolysaccharide-Related Biomarkers in Sepsis.

Sepsis, a life-threatening condition triggered by dysregulated host response to infection, poses significant global health challenges. Identifying lip...