☆ 3.8 Proceedings Paper

AI-based Models for SARS-CoV-2 Severity Scores using Multiple Chest X-Ray Image Features

2022 37TH INTERNATIONAL TECHNICAL CONFERENCE ON CIRCUITS/SYSTEMS, COMPUTERS AND COMMUNICATIONS (ITC-CSCC 2022) (2022)

COVID-Net CXR-S: Deep Convolutional Neural Network for Severity Assessment of COVID-19 Cases from Chest X-ray Images

Hossein Aboutalebi et al.

Summary: This study introduces COVID-Net CXR-S, a convolutional neural network for predicting the severity of lung abnormalities in chest X-ray images of SARS-CoV-2 positive patients. Experimental results show that the network has the potential to be a powerful tool for computer-aided severity assessment. The ultimate goal of this research is to facilitate the development of innovative clinical decision support solutions to assist clinicians in managing the ongoing pandemic.

DIAGNOSTICS (2022)

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Article Multidisciplinary Sciences

Towards computer-aided severity assessment via deep neural networks for geographic and opacity extent scoring of SARS-CoV-2 chest X-rays

A. Wong et al.

Summary: In this study, a deep learning system, COVID-Net S, was assessed for computer-aided scoring of CXRs to evaluate the severity of SARS-CoV-2 lung disease. The deep neural networks showed promising results with good correlation between predicted scores and radiologist scores, indicating potential for effective assessment of SARS-CoV-2 lung disease severity.

SCIENTIFIC REPORTS (2021)

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Article Multidisciplinary Sciences

COVID-Net: a tailored deep convolutional neural network design for detection of COVID-19 cases from chest X-ray images

Linda Wang et al.

SCIENTIFIC REPORTS (2020)

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Article Medicine, General & Internal

Predicting COVID-19 Pneumonia Severity on Chest X-ray With Deep Learning

Joseph Paul Cohen et al.

CUREUS JOURNAL OF MEDICAL SCIENCE (2020)

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Article Respiratory System

Severity scoring of lung oedema on the chest radiograph is associated with clinical outcomes in ARDS

Melissa A. Warren et al.

THORAX (2018)

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AI-based Models for SARS-CoV-2 Severity Scores using Multiple Chest X-Ray Image Features

相关参考文献

COVID-Net CXR-S: Deep Convolutional Neural Network for Severity Assessment of COVID-19 Cases from Chest X-ray Images

Towards computer-aided severity assessment via deep neural networks for geographic and opacity extent scoring of SARS-CoV-2 chest X-rays

COVID-Net: a tailored deep convolutional neural network design for detection of COVID-19 cases from chest X-ray images

Predicting COVID-19 Pneumonia Severity on Chest X-ray With Deep Learning

Severity scoring of lung oedema on the chest radiograph is associated with clinical outcomes in ARDS

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