Critical Care

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

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Federated learning for predicting clinical outcomes in patients with COVID-19.

Federated learning (FL) is a method used for training artificial intelligence models with data from ...

Machine Learning Accelerated, High Throughput, Multi-Objective Optimization of Multiprincipal Element Alloys.

Multiprincipal element alloys (MPEAs) have gained surging interest due to their exceptional properti...

Wearable RF Near-Field Cough Monitoring by Frequency-Time Deep Learning.

Coughing is a common symptom for many respiratory disorders, and can spread droplets of various size...

Predicting clinical outcomes in COVID-19 using radiomics on chest radiographs.

OBJECTIVES: For optimal utilization of healthcare resources, there is a critical need for early iden...

DMC-Fusion: Deep Multi-Cascade Fusion With Classifier-Based Feature Synthesis for Medical Multi-Modal Images.

Multi-modal medical image fusion is a challenging yet important task for precision diagnosis and sur...

Automated segmentation of biventricular contours in tissue phase mapping using deep learning.

Tissue phase mapping (TPM) is an MRI technique for quantification of regional biventricular myocardi...

Evolutionary Multi-Objective One-Shot Filter Pruning for Designing Lightweight Convolutional Neural Network.

Deep neural networks have achieved significant development and wide applications for their amazing p...

5G-enabled contactless multi-user presence and activity detection for independent assisted living.

Wireless sensing is the state-of-the-art technique for next generation health activity monitoring. S...

Multi-feature data repository development and analytics for image cosegmentation in high-throughput plant phenotyping.

Cosegmentation is a newly emerging computer vision technique used to segment an object from the back...

Multi-model fusion of classifiers for blood pressure estimation.

Prehypertension is a new risky disease defined in the seventh report issued by the Joint National Co...

Use of a Digital Chronic Obstructive Pulmonary Disease Respiratory Tracker in a Primary Care Setting: A Feasibility Study.

INTRODUCTION: Telemonitoring is a promising self-management strategy to improve health care outcomes...

Improved protein relative solvent accessibility prediction using deep multi-view feature learning framework.

The accurate prediction of the relative solvent accessibility of a protein is critical to understand...

Accurate diagnosis of sepsis using a neural network: Pilot study using routine clinical variables.

BACKGROUND AND OBJECTIVES: Sepsis is a severe infection that increases mortality risk and is one if ...

Dual Attention Multi-Instance Deep Learning for Alzheimer's Disease Diagnosis With Structural MRI.

Structural magnetic resonance imaging (sMRI) is widely used for the brain neurological disease diagn...

Cross-Modality Interaction Network for Equine Activity Recognition Using Imbalanced Multi-Modal Data.

With the recent advances in deep learning, wearable sensors have increasingly been used in automated...

Observer-based event-triggered control for zero-sum games of input constrained multi-player nonlinear systems.

In this paper, an event-triggered control (ETC) method is investigated to solve zero-sum game (ZSG) ...

Respiratory sound classification for crackles, wheezes, and rhonchi in the clinical field using deep learning.

Auscultation has been essential part of the physical examination; this is non-invasive, real-time, a...

Two-phase non-invasive multi-disease detection via sublingual region.

Non-invasive multi-disease detection is an active technology that detects human diseases automatical...

Refined UNet v3: Efficient end-to-end patch-wise network for cloud and shadow segmentation with multi-channel spectral features.

Semantic segmentation is one of the essential prerequisites for computer vision tasks, but edge-prec...

Dual scope method: A novel application of a simultaneous multi-image display system for a thoracoscopic robotic lobectomy.

The advantages of a multi-input display system platform in robotic thoracic surgery have not been we...

Nasopharyngeal metabolomics and machine learning approach for the diagnosis of influenza.

BACKGROUND: Respiratory virus infections are significant causes of morbidity and mortality, and may ...

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