Critical Care

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

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Protein Fold Recognition Based on Auto-Weighted Multi-View Graph Embedding Learning Model.

Protein fold recognition is critical for studies of the protein structure prediction and drug design...

Multi-Label Classification Scheme Based on Local Regression for Retinal Vessel Segmentation.

Segmenting small retinal vessels with width less than 2 pixels in fundus images is a challenging tas...

Deep multi-instance transfer learning for pneumothorax classification in chest X-ray images.

PURPOSE: Pneumothorax is a life-threatening emergency that requires immediate treatment. Frontal-vie...

Hybrid Random Forest and Support Vector Machine Modeling for HVAC Fault Detection and Diagnosis.

The malfunctioning of the heating, ventilating, and air conditioning (HVAC) system is considered to ...

Development of a Novel Anesthesia Airway Management Robot.

Non-invasive positive pressure ventilation has attracted increasing attention for air management in ...

A contextual multi-task neural approach to medication and adverse events identification from clinical text.

Effective wide-scale pharmacovigilance calls for accurate named entity recognition (NER) of medicati...

Comparative Analysis for Prediction of Kidney Disease Using Intelligent Machine Learning Methods.

Chronic kidney disease (CKD) is a major burden on the healthcare system because of its increasing pr...

Real-Time Arrhythmia Detection Using Hybrid Convolutional Neural Networks.

Background Accurate detection of arrhythmic events in the intensive care units (ICU) is of paramount...

GroningenNet: Deep Learning for Low-Magnitude Earthquake Detection on a Multi-Level Sensor Network.

Automatic detection of low-magnitude earthquakes has become an increasingly important research topic...

Heterogeneous Multi UAV Mission Planning Based on Ant Colony Algorithm Powered BP Neural Network.

With the development of modern science and technology, the field of UAV has also entered the era of ...

Preclinical Evaluation of a New ECCO2R Setup.

Low flow extracorporeal carbon dioxide removal (ECCO2R) is a promising approach to correct hypercapn...

Application of Deep Learning Technology in Predicting the Risk of Inpatient Death in Intensive Care Unit.

The Intensive Care Unit (ICU) is an important unit for the rescue of critically ill patients in hosp...

RespiraTox - Development of a QSAR model to predict human respiratory irritants.

Respiratory irritation is an important human health endpoint in chemical risk assessment. There are ...

Deep Neural Network With Consistency Regularization of Multi-Output Channels for Improved Tumor Detection and Delineation.

Deep learning is becoming an indispensable tool for imaging applications, such as image segmentation...

Deep neural models for automated multi-task diagnostic scan management-quality enhancement, view classification and report generation.

The detailed physiological perspectives captured by medical imaging provides actionable insights to ...

Development of a Machine learning image segmentation-based algorithm for the determination of the adequacy of Gram-stained sputum smear images.

BACKGROUND: Machine learning (ML) prepares and trains a model through supervised or unsupervised lea...

Intelligent Monitoring of Care Status for COPD Patients Based on Deep Learning.

To discuss the application method and effect of COPD patients in deep learning in intelligent monito...

Influence of Critical Care Transport Ventilator Management on Intensive Care Unit Care.

OBJECTIVE: High tidal volume ventilation is associated with ventilator-induced lung injury. Early in...

Vegetation Types Mapping Using Multi-Temporal Landsat Images in the Google Earth Engine Platform.

Vegetation Types (VTs) are important managerial units, and their identification serves as essential ...

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