Critical Care

Latest AI and machine learning research in critical care for healthcare professionals.

7,413 articles
Stay Ahead - Weekly Critical Care research updates
Subscribe
Browse Specialties
Subcategories: Sepsis
Showing 547-567 of 7,413 articles
Constructing an early warning model for elderly sepsis patients based on machine learning.

Sepsis is a serious threat to human life. Early prediction of high-risk populations for sepsis is ne...

Large Language Model-Driven Knowledge Graph Construction in Sepsis Care Using Multicenter Clinical Databases: Development and Usability Study.

BACKGROUND: Sepsis is a complex, life-threatening condition characterized by significant heterogenei...

Temporal and spatial feature extraction using graph neural networks for multi-point water quality prediction in river network areas.

Deep learning methods have demonstrated strong capabilities in capturing nonlinear relationships for...

Role of physics-informed constraints in real-time estimation of 3D vascular fluid dynamics using multi-case neural network.

Numerical simulations of fluid dynamics in tube-like structures are important to biomedical research...

Deep neural networks excel in COVID-19 disease severity prediction-a meta-regression analysis.

COVID-19 is a disease in which early prognosis of severity is critical for desired patient outcomes ...

AI-powered model for predicting mortality risk in VA-ECMO patients: a multicenter cohort study.

Veno-arterial extracorporeal membrane oxygenation (VA-ECMO) is a critical life support technology fo...

Post-Anesthesia Care Unit (PACU) readiness predictions using machine learning: a comparative study of algorithms.

INTRODUCTION: Accurate and timely discharge from the Post-Anesthesia Care Unit (PACU) is essential t...

Multi-center study: ultrasound-based deep learning features for predicting Ki-67 expression in breast cancer.

Applying deep learning algorithms to mine ultrasound features of breast cancer and construct a machi...

Machine Learning-Based VO Estimation Using a Wearable Multiwavelength Photoplethysmography Device.

The rate of oxygen consumption, which is measured as the volume of oxygen consumed per mass per minu...

Bio-inspired neural networks with central pattern generators for learning multi-skill locomotion.

Biological neural circuits, central pattern generators (CPGs), located at the spinal cord are the un...

BSA-Seg: A Bi-level sparse attention network combining narrow band loss for multi-target medical image segmentation.

Segmentation of multiple targets of varying sizes within medical images is of significant importance...

CasPro-ESM2: Accurate identification of Cas proteins integrating pre-trained protein language model and multi-scale convolutional neural network.

Cas proteins (CRISPR-associated protein) are the core components of the CRISPR-Cas system, playing c...

Explainable SHAP-XGBoost models for pressure injuries among patients requiring with mechanical ventilation in intensive care unit.

pressure injuries are significant concern for ICU patients on mechanical ventilation. Early predicti...

Multi-modal MRI synthesis with conditional latent diffusion models for data augmentation in tumor segmentation.

Multimodality is often necessary for improving object segmentation tasks, especially in the case of ...

Student dropout prediction through machine learning optimization: insights from moodle log data.

Student attrition and academic failure remain pervasive challenges in education, often occurring at ...

TSCMamba: Mamba Meets Multi-View Learning for Time Series Classification.

Multivariate time series classification (TSC) is critical for various applications in fields such as...

PyGlaucoMetrics: A Stacked Weight-Based Machine Learning Approach for Glaucoma Detection Using Visual Field Data.

: Glaucoma (GL) classification is crucial for early diagnosis and treatment, yet relying solely on s...

Browse Specialties