Critical Care

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

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Subcategories: Sepsis
Showing 715-735 of 7,422 articles
A Multi-View Feature-Based Interpretable Deep Learning Framework for Drug-Drug Interaction Prediction.

Drug-drug interactions (DDIs) can result in deleterious consequences when patients take multiple med...

Semi-supervised learning for multi-view and non-graph data using Graph Convolutional Networks.

Semi-supervised learning with a graph-based approach has become increasingly popular in machine lear...

Weakly supervised multi-modal contrastive learning framework for predicting the HER2 scores in breast cancer.

Human epidermal growth factor receptor 2 (HER2) is an important biomarker for prognosis and predicti...

Multi-modal dataset creation for federated learning with DICOM-structured reports.

Purpose Federated training is often challenging on heterogeneous datasets due to divergent data stor...

An explainable deep learning model for diabetic foot ulcer classification using swin transformer and efficient multi-scale attention-driven network.

Diabetic Foot Ulcer (DFU) is a severe complication of diabetes mellitus, resulting in significant he...

Pan-sharpening via Symmetric Multi-Scale Correction-Enhancement Transformers.

Pan-sharpening is a widely employed technique for enhancing the quality and accuracy of remote sensi...

Multi-knowledge informed deep learning model for multi-point prediction of Alzheimer's disease progression.

The diagnosis of Alzheimer's disease (AD) based on visual features-informed by clinical knowledge ha...

SDR-Former: A Siamese Dual-Resolution Transformer for liver lesion classification using 3D multi-phase imaging.

Automated classification of liver lesions in multi-phase CT and MR scans is of clinical significance...

Efficient diagnosis of retinal disorders using dual-branch semi-supervised learning (DB-SSL): An enhanced multi-class classification approach.

The early diagnosis of retinal disorders is essential in preventing permanent or partial blindness. ...

Leveraging deep-learning and unconventional data for real-time surveillance, forecasting, and early warning of respiratory pathogens outbreak.

BACKGROUND: Controlling re-emerging outbreaks such as COVID-19 is a critical concern to global healt...

Multi-branch convolutional neural network with cross-attention mechanism for emotion recognition.

Research on emotion recognition is an interesting area because of its wide-ranging applications in e...

Machine Learning Tool for New Selective Serotonin and Serotonin-Norepinephrine Reuptake Inhibitors.

Depression, a serious mood disorder, affects about 5% of the population. Currently, there are two gr...

The intuitionistic fuzzy linguistic assessment of forest soil quality with multi-granularity qualitative information.

The soil quality of forest land is directly related to the growth of forest trees and the local ecol...

High resolution multi-delay arterial spin labeling with self-supervised deep learning denoising for pediatric choroid plexus perfusion MRI.

Choroid plexus (CP) is an important brain structure that produces cerebrospinal fluid (CSF). CP perf...

User-Oriented Requirements for Artificial Intelligence-Based Clinical Decision Support Systems in Sepsis: Protocol for a Multimethod Research Project.

BACKGROUND: Artificial intelligence (AI)-based clinical decision support systems (CDSS) have been de...

Detection of Breath Nitric Oxide at Ppb Level Based on Multiperiodic Spectral Reconstruction Neural Network.

As breath nitric oxide (NO) is a biomarker of respiratory inflammation, reliable techniques for the ...

Self-critical strategy adjustment based artificial intelligence method in generating diagnostic reports of respiratory diseases.

. Humanity faces many health challenges, among which respiratory diseases are one of the leading cau...

TDAG: A multi-agent framework based on dynamic Task Decomposition and Agent Generation.

The emergence of Large Language Models (LLMs) like ChatGPT has inspired the development of LLM-based...

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