Intensivists

From promise to practice: A roadmap for artificial intelligence in critical care.

Artificial intelligence (AI) has regained strong momentum in medicine, driven by unprecedented compu...

Toward Standardized ICU Trauma Resuscitation via Markov Decision Processes.

OBJECTIVE: Guideline-based recommendations for posthemostasis resuscitation in trauma patients remai...

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 ha...

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...

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 transf...

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 platf...

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 ...

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 elusi...

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 prolong...

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

This study presents FCRNet, a Fast Fourier Convolution Residual Network, tailored for fault diagnosi...

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...

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

Artificial Intelligence (AI) is rapidly transforming the landscape of critical care, offering opport...

ICU scoring systems: current perspectives and future directions.

PURPOSE OF REVIEW: This review aims to summarize the recent publications and future perspectives on ...

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 sever...

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 hea...

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 ...

Developing a Panel of Shared Susceptibility Genes as Diagnostic Biomarkers for chronic obstructive pulmonary disease and Heart Failure.

AIM: Chronic obstructive pulmonary disease (COPD) and heart failure (HF) are closely intertwined com...

5-Hydroxymethylcytosine signatures as diagnostic biomarkers for septic cardiomyopathy.

At present, there are currently no molecular biomarkers for the early diagnosis of sepsis cardiomyop...

The emerging role of artificial intelligence in heart failure.

Heart Failure is a prevalent disease with significant impacts on morbidity and mortality. Heart fail...

Machine learning for the prediction of urosepsis using electronic health record data.

Urosepsis, a medical condition resulting from the progression of urinary tract infection (UTI), is a...