Critical Care

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

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Showing 1429-1449 of 7,427 articles
Classification of the quality of canine and feline ventrodorsal and dorsoventral thoracic radiographs through machine learning.

Thoracic radiographs are an essential diagnostic tool in companion animal medicine and are frequentl...

Resolution of tonic concentrations of highly similar neurotransmitters using voltammetry and deep learning.

With advances in our understanding regarding the neurochemical underpinnings of neurological and psy...

Predicting clinical outcomes of SARS-CoV-2 infection during the Omicron wave using machine learning.

The Omicron SARS-CoV-2 variant continues to strain healthcare systems. Developing tools that facilit...

MLMFNet: A multi-level modality fusion network for multi-modal accelerated MRI reconstruction.

Magnetic resonance imaging produces detailed anatomical and physiological images of the human body t...

Attention-based convolutional neural network with multi-modal temporal information fusion for motor imagery EEG decoding.

Convolutional neural network (CNN) has been widely applied in motor imagery (MI)-based brain compute...

Application of interpretable machine learning algorithms to predict acute kidney injury in patients with cerebral infarction in ICU.

BACKGROUND: Acute kidney injury (AKI) is not only a complication but also a serious threat to patien...

All you need is data preparation: A systematic review of image harmonization techniques in Multi-center/device studies for medical support systems.

BACKGROUND AND OBJECTIVES: Artificial intelligence (AI) models trained on multi-centric and multi-de...

Precision medicine in colorectal cancer: Leveraging multi-omics, spatial omics, and artificial intelligence.

Colorectal cancer (CRC) is a leading cause of cancer-related deaths. Recent advancements in genomic ...

Optimizing Image Enhancement: Feature Engineering for Improved Classification in AI-Assisted Artificial Retinas.

Artificial retinas have revolutionized the lives of many blind people by enabling their ability to p...

COVID-19 Hierarchical Classification Using a Deep Learning Multi-Modal.

Coronavirus disease 2019 (COVID-19), originating in China, has rapidly spread worldwide. Physicians ...

A single-joint multi-task motor imagery EEG signal recognition method based on Empirical Wavelet and Multi-Kernel Extreme Learning Machine.

BACKGROUND: In the pursuit of finer Brain-Computer Interface commands, research focus has shifted to...

DeepOCR: A multi-species deep-learning framework for accurate identification of open chromatin regions in livestock.

A wealth of experimental evidence has suggested that open chromatin regions (OCRs) are involved in m...

Intelligent and sustainable waste classification model based on multi-objective beluga whale optimization and deep learning.

Resource recycling is considered necessary for sustainable development, especially in smart cities w...

Attention-based deep convolutional neural network for classification of generalized and focal epileptic seizures.

Epilepsy affects over 50 million people globally. Electroencephalography is critical for epilepsy di...

Multi-modal long document classification based on Hierarchical Prompt and Multi-modal Transformer.

In the realm of long document classification (LDC), previous research has predominantly focused on m...

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