Intensivists

Multi-component collaborative design yields robust hydrogel sensors with superior environmental adaptability for machine learning-assisted gesture recognition.

Developing high-performance wearable flexible sensors that can adapt well to complex environments has become a hotspot. Herein, a polyvinyl alcohol based composite hydrogel sensor with high mechanical strength, desirable frost/swelling resistance, and highly sensitive sensing performance was proposed by a multi-component collaborative design strategy. Meanwhile, an intelligent gesture recognition ...

Real-Time Super-Resolution Ultrasound Imaging for Monitoring Tumor Response During Intensive Care Management of Oncologic Emergencies.

BACKGROUND: Oncologic emergencies in critically ill cancer patients frequently require rapid, real-time assessment of tumor responses to therapeutic interventions. However, conventional imaging modalities such as computed tomography and magnetic resonance imaging are often impractical in intensive care units (ICUs) due to logistical constraints and patient instability. Super-resolution ultrasound ...

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 re...

Unsupervised machine learning to explore inflammation following cardiopulmonary bypass.

IntroductionCardiac surgery with cardiopulmonary bypass (CPB) often induces systemic inflammatory reaction syndrome (SIRS), affecting postoperative ou...

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...

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...

Multicenter Machine Learning-Based Prediction of Mortality in ICU Patients With Hypocalcemia.

BACKGROUND: Hypocalcemia occurs frequently in intensive care units (ICUs) and is independently associated with excess mortality. Conventional severity...

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...

Accelerated brain magnetic resonance imaging with deep learning reconstruction: a comparative study on image quality in pediatric neuroimaging.

BACKGROUND: Magnetic resonance imaging (MRI) is crucial in pediatric radiology; however, the prolonged scan time is a major drawback that often requir...

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.

Identifying propionate metabolism-related genes as biomarkers of sepsis development and therapeutic targets.

The treatment of sepsis is challenging due to unclear mechanisms. Propionate is increasingly seen as critical to sepsis pathophysiology by bridging gu...

Implementing Artificial Intelligence in Critical Care Medicine: a consensus of 22.

Artificial Intelligence (AI) is rapidly transforming the landscape of critical care, offering opportunities for enhanced diagnostic precision and pers...

ICU scoring systems: current perspectives and future directions.

PURPOSE OF REVIEW: This review aims to summarize the recent publications and future perspectives on the use of ICU scoring systems mainly for the asse...

Role of artificial intelligence in ICU therapeutic decision-making for severe infections.

PURPOSE OF REVIEW: To discuss current and future role of artificial intelligence in predicting severe infections and supporting decisions on antibioti...

Improving AI-Based Clinical Decision Support Systems and Their Integration Into Care From the Perspective of Experts: Interview Study Among Different Stakeholders.

BACKGROUND: Artificial intelligence (AI)-based systems are receiving increasing attention in the health care sector. While the use of AI is well advan...

Vibration-based gearbox fault diagnosis using a multi-scale convolutional neural network with depth-wise feature concatenation.

This article proposes a novel approach for vibration-based gearbox fault diagnosis using a multi-scale convolutional neural network with depth-wise fe...

Combination of machine learning and protein‑protein interaction network established one ATM‑DPP4‑TXN ferroptotic diagnostic model with experimental validation.

Ferroptosis and lethal sepsis are interlinked, although this association remains largely unknown to clinical panels. Sepsis is characterized by dysfun...