Critical Care

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

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Subcategories: Sepsis
Showing 64-84 of 7,402 articles
Artificially intelligent nasal perception for rapid sepsis diagnostics.

Sepsis, a life-threatening disease caused by infection, presents a major global health challenge due...

Vox-MMSD: Voxel-wise Multi-scale and Multi-modal Self-Distillation for Self-supervised Brain Tumor Segmentation.

Many deep learning methods have been proposed for brain tumor segmentation from multi-modal Magnetic...

A Semi-supervised Reinforcement Learning Framework Incorporating the Multi-scale IncepMambaNet Network for Glaucoma Progression Prediction.

Glaucoma is the leading cause of irreversible blindness worldwide. Currently, artificial intelligenc...

Multi-camera spatiotemporal deep learning framework for real-time abnormal behavior detection in dense urban environments.

The emerging density in today's urban environments requires a strong multi-camera architecture for r...

Large-vocabulary forensic pathological analyses via prototypical cross-modal contrastive learning.

Forensic pathology plays a vital role in determining the cause and manner of death through macroscop...

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...

Federated fault diagnosis method for collaborative self-diagnosis and cross-robot peer diagnosis.

In multi-robot collaboration, individual failures can propagate to other robots due to the topologic...

Dual-Wavelength Synaptic Simulator ReS/TaNiSe for Multi-Timescale Learning in Neuromorphic Computing.

To address the limitations of silicon-based devices in neuromorphic computing, this study proposes a...

Early detection of ICU-acquired infections using high-frequency electronic health record data.

BACKGROUND: Nosocomial infections are a major cause of morbidity and mortality in the ICU. Earlier i...

MDNCT: a multi-domain neurocognitive transformer architecture approach for early prediction of autism spectrum disorders.

Intellectual disability (ID) refers to a disorder involving intelligence and adaptive behavior that ...

Multi-scale feature fusion keypoint detection network for ship draft line localization.

In the maritime industry, accurately detecting a ship's draft line is crucial for ensuring transacti...

Development and validation of a nomogram model to predict postoperative delirium after resection of esophageal cancer.

The study aimed to establish and validate a nomogram model to predict postoperative delirium (POD) a...

Artificial intelligence platform to predict children's hospital care for respiratory disease using clinical, pollution, and climatic factors.

BACKGROUND: Hospitals and health care systems may benefit from artificial intelligence (AI) and big ...

An illustration of multi-class roc analysis for predicting internet addiction among university students.

The internet is one of the essential tools today, and its impact is particularly felt among universi...

Analysis of aPTT predictors after unfractionated heparin administration in intensive care units using machine learning models.

OBJECTIVES: Predicting optimal coagulation control using heparin in intensive care units (ICUs) rema...

Auto-embedding transformer under multi-source information fusion for few-shot fault diagnosis.

Data-driven intelligent fault diagnosis methods have become essential for ensuring the reliability a...

A defense method against multi-label poisoning attacks in federated learning.

Federated learning is a distributed machine learning framework that allows multiple parties to colla...

Multi robot exploration using an advanced multi-objective salp swarm algorithm for efficient coverage and performance.

This work introduces the Advanced Multi-Objective Salp Swarm Algorithm Exploration Technique (AMET),...

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