[HTML][HTML] Application of machine learning in CT images and X-rays of COVID-19 pneumonia

F Zhang - Medicine, 2021 - journals.lww.com
Abstract Coronavirus disease (COVID-19) has spread worldwide. X-ray and computed
tomography (CT) are 2 technologies widely used in image acquisition, segmentation …

Artificial intelligence-driven assessment of radiological images for COVID-19

Y Bouchareb, PM Khaniabadi, F Al Kindi… - Computers in biology …, 2021 - Elsevier
Artificial Intelligence (AI) methods have significant potential for diagnosis and prognosis of
COVID-19 infections. Rapid identification of COVID-19 and its severity in individual patients …

COVID-19 prognostic modeling using CT radiomic features and machine learning algorithms: Analysis of a multi-institutional dataset of 14,339 patients

I Shiri, Y Salimi, M Pakbin, G Hajianfar, AH Avval… - Computers in biology …, 2022 - Elsevier
Background We aimed to analyze the prognostic power of CT-based radiomics models
using data of 14,339 COVID-19 patients. Methods Whole lung segmentations were …

Methodology-centered review of molecular modeling, simulation, and prediction of SARS-CoV-2

K Gao, R Wang, J Chen, L Cheng, J Frishcosy… - Chemical …, 2022 - ACS Publications
Despite tremendous efforts in the past two years, our understanding of severe acute
respiratory syndrome coronavirus 2 (SARS-CoV-2), virus–host interactions, immune …

High-dimensional multinomial multiclass severity scoring of COVID-19 pneumonia using CT radiomics features and machine learning algorithms

I Shiri, S Mostafaei, A Haddadi Avval, Y Salimi… - Scientific reports, 2022 - nature.com
We aimed to construct a prediction model based on computed tomography (CT) radiomics
features to classify COVID-19 patients into severe-, moderate-, mild-, and non-pneumonic. A …

COVID-19 classification of X-ray images using deep neural networks

D Keidar, D Yaron, E Goldstein, Y Shachar, A Blass… - European …, 2021 - Springer
Objectives In the midst of the coronavirus disease 2019 (COVID-19) outbreak, chest X-ray
(CXR) imaging is playing an important role in diagnosis and monitoring of patients with …

Diagnosis of COVID-19 using CT image radiomics features: a comprehensive machine learning study involving 26,307 patients

I Shiri, Y Salimi, A Saberi, M Pakbin, G Hajianfar… - medRxiv, 2021 - medrxiv.org
Purpose To derive and validate an effective radiomics-based model for differentiation of
COVID-19 pneumonia from other lung diseases using a very large cohort of patients …

Effects of prone ventilation on oxygenation, inflammation, and lung infiltrates in COVID-19 related acute respiratory distress syndrome: a retrospective cohort study

R Khullar, S Shah, G Singh, J Bae, R Gattu… - Journal of clinical …, 2020 - mdpi.com
Patients receiving mechanical ventilation for coronavirus disease 2019 (COVID-19) related,
moderate-to-severe acute respiratory distress syndrome (CARDS) have mortality rates …

Chest X‐ray lung imaging features in pediatric COVID‐19 and comparison with viral lower respiratory infections in young children

G Nino, J Molto, H Aguilar, J Zember… - Pediatric …, 2021 - Wiley Online Library
Rationale Chest radiography (CXR) is a noninvasive imaging approach commonly used to
evaluate lower respiratory tract infections (LRTIs) in children. However, the specific imaging …

Covid-19 classification of x-ray images using deep neural networks

E Goldstein, D Keidar, D Yaron, Y Shachar… - arXiv preprint arXiv …, 2020 - arxiv.org
In the midst of the coronavirus disease 2019 (COVID-19) outbreak, chest X-ray (CXR)
imaging is playing an important role in the diagnosis and monitoring of patients with COVID …