Hospital-Based Medicine

Intensivists

Latest AI and machine learning research in intensivists for healthcare professionals.

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Arrhythmia classification based on multi-input convolutional neural network with attention mechanism.

Arrhythmia is a prevalent cardiac disorder that can lead to severe complications such as stroke and ...

Traumatic brain injury management in the intensive care unit: standard of care and knowledge gaps.

Despite advances in the management of traumatic brain injury (TBI) in the intensive care unit (ICU),...

Harnessing AI in critical care: opportunities, challenges and key steps for success.

BACKGROUND: The integration of artificial intelligence (AI) into critical care offers significant po...

Multi-class transformer-based segmentation of pancreatic ductal adenocarcinoma and surrounding structures in CT imaging: a multi-center evaluation.

OBJECTIVE: Accurate segmentation of pancreatic ductal adenocarcinoma (PDAC) and surrounding anatomic...

MOPSOGAT: Predicting CircRNA-Disease Associations via Improved Multi-objective Particle Swarm Optimization and Graph Attention Network.

Recently increasing researches have discovered that circRNAs are remarkably reliable in organisms an...

Integrated Polarization, Distance, and Rotation for Multi-DoF Diffractive Processor and Information Encryption.

All-optical diffractive deep neural networks (DNNs) offer significant advantages in processing speed...

Exploring the molecular mechanisms of lactylation-related biological functions and immune regulation in sepsis-associated acute kidney injury.

Lactylation, a novel post-translational modification, has been implicated in various pathophysiologi...

The future of healthcare-associated infection surveillance: Automated surveillance and using the potential of artificial intelligence.

Healthcare-associated infections (HAIs) are common adverse events, and surveillance is considered a ...

Predicting carbapenem-resistant Pseudomonas aeruginosa infection risk using XGBoost model and explainability.

The prevalence and spread of carbapenem-resistant Pseudomonas aeruginosa (CRPA) is a global public h...

Machine learning-based prediction of respiratory depression during sedation for liposuction.

Procedural sedation is often performed by non-anesthesiologists in various settings and can lead to ...

Machine learning models for predicting severe acute kidney injury in patients with sepsis-induced myocardial injury.

Severe acute kidney injury (sAKI) is a prevalent and serious complication among patients with sepsis...

A machine learning-based prediction model for sepsis-associated delirium in intensive care unit patients with sepsis-associated acute kidney injury.

Sepsis-associated acute kidney injury (SA-AKI) patients in the ICU often suffer from sepsis-associat...

Multi-view based heterogeneous graph contrastive learning for drug-target interaction prediction.

Drug-Target Interaction (DTI) prediction plays a pivotal role in accelerating drug discovery and dev...

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