Critical Care

Multi-modal orthogonal fusion network via cross-layer guidance for Alzheimer's disease diagnosis.

Multi-modal neuroimaging techniques are widely employed for the accurate diagnosis of Alzheimer's Disease (AD). Existing fusion methods typically focus on capturing semantic correlations between modalities through feature-level interactions. However, they fail to suppress redundant cross-modal information, resulting in sub-optimal multi-modal representation. Moreover, these methods ignore subject-...

Pharmacological Haemodynamic Management in the Intensive Care Unit: The Evolution of the Nurse's Role Over 50 Years.

AIM: To examine the evolution of intensive care nurses' roles in pharmacological haemodynamic management from 1975 to 2025 and to explore projected responsibilities through 2075. DESIGN: A scholarly commentary. METHODS: A critical synthesis of literature, historical accounts and clinical guidelines spanning 1975-2025, focussing on nursing practice, technology, workforce dynamics and patient safety...

Central venous catheters tip positioning: Insights from a retrospective analysis.

BACKGROUND: Tunneled central venous catheters (tCVCs) are essential in hemodialysis when arteriovenous access is not feasible. Their correct positioni...

Explainable machine learning for discontinuation of therapeutic antibiotics in intensive care patients.

INTRODUCTION: The threshold for initiating lifesaving antibiotics for intensive care patients is low while determining when to stop remains challengin...

Computer Vision Detects an Association Between Gross Gill Score and Ventilation Rates in Farmed Atlantic Salmon (Salmo salar).

Poor gill health compromises the health and welfare of farmed Atlantic salmon (Salmo salar) by causing respiratory distress and increased ventilation ...

Convergence: Multi-omics and AI are reshaping the landscape biomedical research.

This special volume of Biochimica et Biophysica Acta - Molecular Basis of Disease showcases a transformative era in biomedical research, driven by the...

Enhancing mechanical ventilation management with AI: Computer vision for automated detection of ventilatory modes, parameters and asynchrony.

PURPOSE: To evaluate the performance of an artificial intelligence (AI)-based decision support platform called NexoVent, which uses computer vision to...

How do experts classify sepsis cases for sepsis surveillance? Lessons learned from a Behavioural Artificial Intelligence Technology (BAIT) approach.

OBJECTIVES: To identify relevant objective variables for retrospective identification of 'suspected infection' and sepsis, using behavioural artificia...

Effect of artificial intelligence in extracorporeal membrane oxygenation: a systematic review and meta-analysis.

OBJECTIVES: To evaluate the effectiveness of Artificial Intelligence (AI) in improving clinical outcomes in Extracorporeal Membrane Oxygenation (ECMO)...

Tissue perfusion pressure: A novel hemodynamic measure to assess risk of acute kidney injury after cardiac surgery.

BACKGROUND: Optimal hemodynamic targets for preventing acute kidney injury (AKI) have remained elusive. We hypothesized that lower tissue perfusion pr...

Integrative analysis of multi-omics data and gut microbiota composition reveals prognostic subtypes and predicts immunotherapy response in colorectal cancer using machine learning.

Colorectal cancer (CRC) exhibits substantial heterogeneity in molecular subtypes and clinical outcomes. We performed an integrative analysis of multi-...

SBC-SHAP: Increasing the Accessibility and Interpretability of Machine Learning Algorithms for Sepsis Prediction.

BACKGROUND: Sepsis is a life-threatening condition that is one of the major causes of death worldwide. Early detection of sepsis is required for fast ...

FCRNet: Fast Fourier convolutional residual network for ventilator bearing fault diagnosis.

This study presents FCRNet, a Fast Fourier Convolution Residual Network, tailored for fault diagnosis of mine ventilation bearings under complex opera...

Early prediction of non-invasive ventilation outcome using the TabPFN machine learning model: a multi-centre validation study.

AI Predictive Model of Mortality and Intensive Care Unit Admission in the COVID-19 Pandemic: Retrospective Population Cohort Study of 12,000 Patients.

BACKGROUND: One of the main challenges with COVID-19 has been that although there are known factors associated with a worse prognosis, clinicians have...

Genome sequencing is critical for forecasting outcomes following congenital cardiac surgery.

While exome and whole genome sequencing have transformed medicine by elucidating the genetic underpinnings of both rare and common complex disorders, ...

A Multi-Scale attention network for building extraction from high-resolution remote sensing images.

The information in remote sensing images often leads to incomplete building contours and suboptimal adaptability to complex building scenes. To addres...

Comprehensive multi-omics and machine learning framework for glioma subtyping and precision therapeutics.

Glioma is a highly heterogeneous and aggressive brain tumour that demands an integrated understanding of its molecular and immunological landscape. We...

Application progress of machine learning in patient-ventilator asynchrony during mechanical ventilation: a systematic review.

INTRODUCTION: Patient-ventilator asynchrony (PVA) is a common and harmful complication during mechanical ventilation, often requiring labor-intensive ...

Automated detection of air trapping from mechanical ventilation waveform through interpretable dual-channel 1D convolutional neural network.

. Air trapping is a major symptom of respiratory diseases like chronic obstructive pulmonary disease and asthma, and has always been a significant pro...