Critical Care

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

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Subcategories: Sepsis
Showing 2038-2058 of 7,427 articles
Classifier for the functional state of the respiratory system via descriptors determined by using multimodal technology.

Currently, intelligent systems built on a multimodal basis are used to study the functional state of...

Predicting risk of sepsis, comparison between machine learning methods: a case study of a Virginia hospital.

Sepsis is an inflammation caused by the body's systemic response to an infection. The infection coul...

Segmentation for Multi-Rock Types on Digital Outcrop Photographs Using Deep Learning Techniques.

The basic identification and classification of sedimentary rocks into sandstone and mudstone are imp...

Dynamic prediction of life-threatening events for patients in intensive care unit.

BACKGROUND: Early prediction of patients' deterioration is helpful in early intervention for patient...

Explainable machine learning methods and respiratory oscillometry for the diagnosis of respiratory abnormalities in sarcoidosis.

BACKGROUND: In this work, we developed many machine learning classifiers to assist in diagnosing res...

Improving myocardial pathology segmentation with U-Net++ and EfficientSeg from multi-sequence cardiac magnetic resonance images.

BACKGROUND: Myocardial pathology segmentation plays an utmost role in the diagnosis and treatment of...

Integrative Serum Metabolic Fingerprints Based Multi-Modal Platforms for Lung Adenocarcinoma Early Detection and Pulmonary Nodule Classification.

Identification of novel non-invasive biomarkers is critical for the early diagnosis of lung adenocar...

Clinical applicability of deep learning-based respiratory signal prediction models for four-dimensional radiation therapy.

For accurate respiration gated radiation therapy, compensation for the beam latency of the beam cont...

Multi-modal contrastive mutual learning and pseudo-label re-learning for semi-supervised medical image segmentation.

Semi-supervised learning has a great potential in medical image segmentation tasks with a few labele...

Multi-Object Detection in Security Screening Scene Based on Convolutional Neural Network.

The technique for target detection based on a convolutional neural network has been widely implement...

Multi-Aspect enhanced Graph Neural Networks for recommendation.

Graph neural networks (GNNs) have achieved remarkable performance in personalized recommendation, fo...

Collaborative Damage Detection Framework for Rail Structures Based on a Multi-Agent System Embedded with Soft Multi-Functional Sensors.

With the rapid growth of railways in China, the focus has changed to the maintenance of large-scale ...

Deep learning of longitudinal chest X-ray and clinical variables predicts duration on ventilator and mortality in COVID-19 patients.

OBJECTIVES: To use deep learning of serial portable chest X-ray (pCXR) and clinical variables to pre...

DeepMPM: a mortality risk prediction model using longitudinal EHR data.

BACKGROUND: Accurate precision approaches have far not been developed for modeling mortality risk in...

Do you need sharpened details? Asking MMDC-Net: Multi-layer multi-scale dilated convolution network for retinal vessel segmentation.

Convolutional neural networks (CNN), especially numerous U-shaped models, have achieved great progre...

Multi-environment robotic transitions through adaptive morphogenesis.

The current proliferation of mobile robots spans ecological monitoring, warehouse management and ext...

Edge-Aware Graph Neural Network for Multi-Hop Path Reasoning over Knowledge Base.

Multi-hop path reasoning over knowledge base aims at finding answer entities for an input question b...

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