Critical Care

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

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Subcategories: Sepsis
Showing 1051-1071 of 7,427 articles
A Multi-level ensemble approach for skin lesion classification using Customized Transfer Learning with Triple Attention.

Skin lesions encompass a variety of skin abnormalities, including skin diseases that affect structur...

Deep learning-based approach for acquisition time reduction in ventilation SPECT in patients after lung transplantation.

We aimed to evaluate the image quality and diagnostic performance of chronic lung allograft dysfunct...

Personalized multi-head self-attention network for news recommendation.

With the rapid explosion of online news and user population, personalized news recommender systems h...

Empirical investigation of multi-source cross-validation in clinical ECG classification.

Traditionally, machine learning-based clinical prediction models have been trained and evaluated on ...

Uncovering the features of industrial odors-derived environmental complaints and proactive countermeasures by using machine-learning.

Industrial odor-derived environmental complaints pose an emerging and far-reaching challenge in citi...

Integrative multi-omic and machine learning approach for prognostic stratification and therapeutic targeting in lung squamous cell carcinoma.

The proliferation, metastasis, and drug resistance of cancer cells pose significant challenges to th...

A multi-class fundus disease classification system based on an adaptive scale discriminator and hybrid loss.

Fundus images are crucial in the observation and detection of ophthalmic diseases. However, detectin...

InstructNet: A novel approach for multi-label instruction classification through advanced deep learning.

People use search engines for various topics and items, from daily essentials to more aspirational a...

Knowledge-driven multi-graph convolutional network for brain network analysis and potential biomarker discovery.

In brain network analysis, individual-level data can provide biological features of individuals, whi...

Is artificial intelligence prepared for the 24-h shifts in the ICU?

Integrating machine learning (ML) into intensive care units (ICUs) can significantly enhance patient...

An AI Agent for Fully Automated Multi-Omic Analyses.

With the fast-growing and evolving omics data, the demand for streamlined and adaptable tools to han...

Self-adaptive label discovery and multi-view fusion for complementary label learning.

Unlike traditional supervised classification, complementary label learning (CLL) operates under a we...

Development and validation of a sepsis risk index supporting early identification of ICU-acquired sepsis: an observational study.

BACKGROUND: Sepsis is a threat to global health, and domestically is the major cause of in-hospital ...

MobileNet-V2: An Enhanced Skin Disease Classification by Attention and Multi-Scale Features.

The increasing prevalence of skin diseases necessitates accurate and efficient diagnostic tools. Thi...

PViT-AIR: Puzzling vision transformer-based affine image registration for multi histopathology and faxitron images of breast tissue.

Breast cancer is a significant global public health concern, with various treatment options availabl...

MMF-NNs: Multi-modal Multi-granularity Fusion Neural Networks for brain networks and its application to epilepsy identification.

Structural and functional brain networks are generated from two scan sequences of magnetic resonance...

Using random forest and biomarkers for differentiating COVID-19 and Mycoplasma pneumoniae infections.

The COVID-19 pandemic has underscored the critical need for precise diagnostic methods to distinguis...

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