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Role of artificial intelligence in COVID-19 detection
The global pandemic of coronavirus disease (COVID-19) has caused millions of deaths and
affected the livelihood of many more people. Early and rapid detection of COVID-19 is a …
affected the livelihood of many more people. Early and rapid detection of COVID-19 is a …
A convolutional neural network architecture for segmentation of lung diseases using chest X-ray images
The segmentation of lungs from medical images is a critical step in the diagnosis and
treatment of lung diseases. Deep learning techniques have shown great promise in …
treatment of lung diseases. Deep learning techniques have shown great promise in …
[HTML][HTML] Automatic lung segmentation algorithm on chest x-ray images based on fusion variational auto-encoder and three-terminal attention mechanism
F Cao, H Zhao - Symmetry, 2021 - mdpi.com
Automatic segmentation of the lungs in Chest X-ray images (CXRs) is a key step in the
screening and diagnosis of related diseases. There are many opacities in the lungs in the …
screening and diagnosis of related diseases. There are many opacities in the lungs in the …
Deep Learning-Based Classification and Semantic Segmentation of Lung Tuberculosis Lesions in Chest X-ray Images
CY Ou, IY Chen, HT Chang, CY Wei, DY Li, YK Chen… - Diagnostics, 2024 - mdpi.com
We present a deep learning (DL) network-based approach for detecting and semantically
segmenting two specific types of tuberculosis (TB) lesions in chest X-ray (CXR) images. In …
segmenting two specific types of tuberculosis (TB) lesions in chest X-ray (CXR) images. In …
[HTML][HTML] A hybrid decision tree and deep learning approach combining medical imaging and electronic medical records to predict intubation among hospitalized …
Background: Early prediction of the need for invasive mechanical ventilation (IMV) in
patients hospitalized with COVID-19 symptoms can help in the allocation of resources …
patients hospitalized with COVID-19 symptoms can help in the allocation of resources …
Development and Validation of a Deep Learning Classifier Using Chest Radiographs to Predict Extubation Success in Patients Undergoing Invasive Mechanical …
The decision to extubate patients on invasive mechanical ventilation is critical; however,
clinician performance in identifying patients to liberate from the ventilator is poor. Machine …
clinician performance in identifying patients to liberate from the ventilator is poor. Machine …
[HTML][HTML] CXR-Seg: A Novel Deep Learning Network for Lung Segmentation from Chest X-Ray Images
S Din, M Shoaib, E Serpedin - Bioengineering, 2025 - mdpi.com
Over the past decade, deep learning techniques, particularly neural networks, have become
essential in medical imaging for tasks like image detection, classification, and segmentation …
essential in medical imaging for tasks like image detection, classification, and segmentation …
[HTML][HTML] Impartially validated multiple deep-chain models to detect COVID-19 in chest X-ray using latent space radiomics
The COVID-19 pandemic continues to spread globally at a rapid pace, and its rapid
detection remains a challenge due to its rapid infectivity and limited testing availability. One …
detection remains a challenge due to its rapid infectivity and limited testing availability. One …
[PDF][PDF] Automatic lung segmentation algorithm on chest X-ray images based on fusion variational auto-encoder and three-terminal attention mechanism. Symmetry …
F Cao, H Zhao - 2021 - pdfs.semanticscholar.org
Automatic segmentation of the lungs in Chest X-ray images (CXRs) is a key step in the
screening and diagnosis of related diseases. There are many opacities in the lungs in the …
screening and diagnosis of related diseases. There are many opacities in the lungs in the …