AIMC Topic: Pneumonia, Viral

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[Identifying Novel Coronavirus Pneumonia With CT Images: A Deep Learning Approach With Detail Upsampling and Attention Guidance].

Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition Mar 20, 2024
OBJECTIVE: To construct a deep learning-based target detection method to help radiologists perform rapid diagnosis of lesions in the CT images of patients with novel coronavirus pneumonia (NCP) by restoring detailed information and mining local infor...
Humans Pandemics COVID-19 Deep Learning Coronavirus Infections Betacoronavirus Pneumonia, Viral Algorithms Tomography, X-Ray Computed SARS-CoV-2
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Advanced Lung Disease Detection: CBAM-Augmented, Lightweight EfficientNetB2 with Visual Insights.

Current medical imaging Jan 1, 2024
INTRODUCTION: This paper presents a multichannel deep-learning method for detecting lung diseases using chest X-ray images. Using EfficientNetB0 through EfficientNetB7 pretrained models, the methodology offers improved performance in classifying COVI...
Humans Radiography, Thoracic COVID-19 Pneumonia, Viral Radiographic Image Interpretation, Computer-Assisted Lung Diseases SARS-CoV-2 Deep Learning
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Prediction of early-phase cytomegalovirus pneumonia in post-stem cell transplantation using a deep learning model.

Technology and health care : official journal of the European Society for Engineering and Medicine Jan 1, 2024
BACKGROUND: Diagnostic challenges exist for CMV pneumonia in post-hematopoietic stem cell transplantation (post-HSCT) patients, despite early-phase radiographic changes.
Hematopoietic Stem Cell Transplantation Pneumonia, Viral Female Adult Male Middle Aged Deep Learning Cytomegalovirus Infections Neural Networks, Computer COVID-19 Tomography, X-Ray Computed Humans
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DKCNN: Improving deep kernel convolutional neural network-based COVID-19 identification from CT images of the chest.

Journal of X-ray science and technology Jan 1, 2024
BACKGROUND: An efficient deep convolutional neural network (DeepCNN) is proposed in this article for the classification of Covid-19 disease.
Neural Networks, Computer Pandemics COVID-19 Humans Deep Learning Image Processing, Computer-Assisted Coronavirus Infections Thorax Algorithms Tomography, X-Ray Computed SARS-CoV-2 Betacoronavirus Pneumonia, Viral
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DDA-SSNets: Dual decoder attention-based semantic segmentation networks for COVID-19 infection segmentation and classification using chest X-Ray images.

Journal of X-ray science and technology Jan 1, 2024
BACKGROUND: COVID-19 needs to be diagnosed and staged to be treated accurately. However, prior studies' diagnostic and staging abilities for COVID-19 infection needed to be improved. Therefore, new deep learning-based approaches are required to aid r...
Radiography, Thoracic Betacoronavirus Pneumonia, Viral Algorithms Deep Learning Humans SARS-CoV-2 Neural Networks, Computer Coronavirus Infections Lung Pandemics Semantics COVID-19
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UBNet: Deep learning-based approach for automatic X-ray image detection of pneumonia and COVID-19 patients.

Journal of X-ray science and technology Jan 1, 2022
BACKGROUND: Analysis of chest X-ray images is one of the primary standards in diagnosing patients with COVID-19 and pneumonia, which is faster than using PCR Swab method. However, accuracy of using X-ray images needs to be improved.
Algorithms SARS-CoV-2 Deep Learning X-Rays Pneumonia, Viral Humans Neural Networks, Computer COVID-19
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Classification by a stacking model using CNN features for COVID-19 infection diagnosis.

Journal of X-ray science and technology Jan 1, 2022
Affecting millions of people all over the world, the COVID-19 pandemic has caused the death of hundreds of thousands of people since its beginning. Examinations also found that even if the COVID-19 patients initially survived the coronavirus, pneumon...
Humans Pneumonia, Viral SARS-CoV-2 Deep Learning Pandemics COVID-19 Testing COVID-19 Algorithms
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Feasibility of Radiomics to Differentiate Coronavirus Disease 2019 (COVID-19) from H1N1 Influenza Pneumonia on Chest Computed Tomography: A Proof of Concept.

Iranian journal of medical sciences Nov 1, 2021
BACKGROUND: Chest computed tomography (CT) plays an essential role in diagnosing coronavirus disease 2019 (COVID-19). However, CT findings are often nonspecific among different viral pneumonia conditions. The differentiation between COVID-19 and infl...
Influenza, Human Humans Influenza A Virus, H1N1 Subtype Artificial Intelligence Pneumonia, Viral Female COVID-19 Male Diagnosis, Differential Retrospective Studies Feasibility Studies Tomography, X-Ray Computed
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Application of machine learning in CT images and X-rays of COVID-19 pneumonia.

Medicine Sep 10, 2021
Coronavirus disease (COVID-19) has spread worldwide. X-ray and computed tomography (CT) are 2 technologies widely used in image acquisition, segmentation, diagnosis, and evaluation. Artificial intelligence can accurately segment infected parts in X-r...
Pneumonia, Viral Tomography, X-Ray Computed Humans SARS-CoV-2 Machine Learning Radiography COVID-19
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FLANNEL (Focal Loss bAsed Neural Network EnsembLe) for COVID-19 detection.

Journal of the American Medical Informatics Association : JAMIA Mar 1, 2021
OBJECTIVE: The study sought to test the possibility of differentiating chest x-ray images of coronavirus disease 2019 (COVID-19) against other pneumonia and healthy patients using deep neural networks.
Diagnosis, Differential Algorithms Radiography, Thoracic Lung Humans ROC Curve Pneumonia, Viral Neural Networks, Computer COVID-19
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