Critical Care

Early heart-rate trajectory phenotypes predict short-term mortality in critically ill patients: a dynamic time-warping cluster analysis.

UNLABELLED: Heart rate (HR) reflects illness severity in critically ill patients, but the prognostic...

Development and Validation of a Machine Learning Model That Uses Voice to Predict Aspiration Risk.

BACKGROUND: Aspiration causes or aggravates a variety of respiratory diseases. Subjective bedside ev...

K-MIMIC: a nationwide Korean multi-institutional Multimodal intensive care dataset.

BACKGROUND: Recent advancements in critical care have highlighted the need for comprehensive, multim...

Comparison of large language models and conventional machine learning in postoperative outcome prediction: a retrospective, multi-national development and validation study.

BACKGROUND: Conventional machine learning (ML) models for predicting surgical outcomes have limitati...

Prediction of Fontan failure and correlates of Fontan-associated liver disease severity using machine learning and radiomic features from multi-parametric abdominal MRI.

BACKGROUND: Fontan-associated liver disease (FALD) is associated with morbidity and mortality in pat...

An Explanation User Interface for Artificial Intelligence-Supported Mechanical Ventilation Optimization for Clinicians: User-Centered Design and Formative Usability Study.

BACKGROUND: The integration of artificial intelligence (AI) into clinical decision support systems (...

Detection of Swallowing Abnormalities in Pediatric FEES Recordings Using Rule-Based and Model-Based Methods.

Pediatric swallowing dysfunction (SwD) poses serious health risks, including aspiration, malnutritio...

Explainable AI for critical care: a systematic review of interpretable models for sepsis and ICU mortality prediction.

A machine learning model for prediction of risk of dementia superimposed on delirium in intensive care patients.

BACKGROUND: The objective of this study was to construct a predictive model using multiple machine l...

Risk Factors for Postoperative Delirium in Nonintensive Care Unit Patients: Machine Learning Approach.

Postoperative delirium is a frequent and serious complication lacking effective prediction tools for...

Explainable multi-modal approach for uncovering key predictors of stroke-risk from ECG, EMG, blood pressure, and respiratory signals.

Accurate and timely stroke-risk prediction is necessary to help patients at risk take guided measure...

Explainable Temporal Inference for Irregular Multivariate Time Series. A Case Study for Early Prediction of Multidrug Resistance.

OBJECTIVE: Many healthcare problems involve complex patient trajectories represented as Multivariate...

A novel, standardised approach to balancing effectiveness, efficiency and utility of surveillance AI prediction models for hospitalised patients using sepsis prediction as an exemplar.

OBJECTIVE: To introduce a novel, standardised approach to evaluating AI prediction models in balanci...

Six-axis robotic extrusion of hybrid hydrogels for biomimetic airway model fabrication.

Respiratory diseases remain a major global health burden, motivating the need for improved experimen...

How do dialysis nurses and AI reason clinically? A scenario-based comparative study.

Neural Network Model for Predicting Oxygen Transfer in Membrane Oxygenators Under Variable Extracorporeal Membrane Oxygenation Conditions.

During extracorporeal membrane oxygenation (ECMO) management, early recognition and intervention are...

Health trajectories of patients with amyotrophic lateral sclerosis before and after initiation of non-invasive ventilation: a French nationwide database analysis.

BACKGROUND: Management of amyotrophic lateral sclerosis (ALS) is complicated by heterogeneous presen...

Early prediction of colonization by carbapenemase-producing enterobacterales at ICU admission using machine learning.

Colonization by carbapenemase-producing Enterobacterales (CPE) on admission to an intensive care uni...

Highly efficient and durable Th1-biased protective immunity from a novel mRNA vaccine against RSV via AI-assisted antigen screening.

Respiratory syncytial virus (RSV) is a leading cause of severe respiratory illness, imposing a signi...

A tri-omics and machine learning framework identifies prognostic biomarkers and metabolic signatures in sepsis.

Sepsis is a complex systemic inflammatory syndrome that currently lacks stable and specific biomarke...

Analysis of differential photoplethysmography signal patterns in apnea and hypopnea.

OBJECTIVE: Photoplethysmography, a non-invasive optical technique that measures changes in blood vol...