Critical Care

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

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Showing 1870-1890 of 7,427 articles
Multi-View Graph Neural Architecture Search for Biomedical Entity and Relation Extraction.

Recently, graph neural architecture search (GNAS) frameworks have been successfully used to automati...

A Multi-Attention Approach for Person Re-Identification Using Deep Learning.

Person re-identification (Re-ID) is a method for identifying the same individual via several non-int...

A hybrid model- and deep learning-based framework for functional lung image synthesis from multi-inflation CT and hyperpolarized gas MRI.

BACKGROUND: Hyperpolarized gas MRI is a functional lung imaging modality capable of visualizing regi...

DeepNAPSI multi-reader nail psoriasis prediction using deep learning.

Nail psoriasis occurs in about every second psoriasis patient. Both, finger and toe nails can be aff...

CSI-Based Human Activity Recognition Using Multi-Input Multi-Output Autoencoder and Fine-Tuning.

Wi-Fi-based human activity recognition (HAR) has gained considerable attention recently due to its e...

De novo drug design based on Stack-RNN with multi-objective reward-weighted sum and reinforcement learning.

CONTEXT: In recent decades, drug development has become extremely important as different new disease...

Enhancing Multi-disease Diagnosis of Chest X-rays with Advanced Deep-learning Networks in Real-world Data.

The current artificial intelligence (AI) models are still insufficient in multi-disease diagnosis fo...

CRMSNet: A deep learning model that uses convolution and residual multi-head self-attention block to predict RBPs for RNA sequence.

RNA-binding proteins (RBPs) play significant roles in many biological life activities, many algorith...

Automated deep learning for classification of dental implant radiographs using a large multi-center dataset.

This study aimed to evaluate the accuracy of automated deep learning (DL) algorithm for identifying ...

Dual center validation of deep learning for automated multi-label segmentation of thoracic anatomy in bedside chest radiographs.

BACKGROUND AND OBJECTIVES: Bedside chest radiographs (CXRs) are challenging to interpret but importa...

Multi CNN based automatic detection of mitotic nuclei in breast histopathological images.

In breast cancer diagnosis, the number of mitotic cells in a specific area is an important measure. ...

Multi-modal body part segmentation of infants using deep learning.

BACKGROUND: Monitoring the body temperature of premature infants is vital, as it allows optimal temp...

Improvement of multi-task learning by data enrichment: application for drug discovery.

Multi-task learning in deep neural networks has become a topic of growing importance in many researc...

Classification of coma/brain-death EEG dataset based on one-dimensional convolutional neural network.

Electroencephalography (EEG) evaluation is an important step in the clinical diagnosis of brain deat...

Co-model for chemical toxicity prediction based on multi-task deep learning.

The toxicity of compounds is closely related to the effectiveness and safety of drug development, an...

Technical Advancements in Abdominal Diffusion-weighted Imaging.

Since its first observation in the 18th century, the diffusion phenomenon has been actively studied ...

A multi-task and multi-channel convolutional neural network for semi-supervised neonatal artefact detection.

. Automated artefact detection in the neonatal electroencephalogram (EEG) is crucial for reliable au...

The effect of soft palate reconstruction with the da Vinci robot on middle ear function in children: an observational study.

Cleft palate is associated with a high prevalence of middle ear dysfunction, even after palatal repa...

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