Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
Abstract Machine learning methods offer great promise for fast and accurate detection and
prognostication of coronavirus disease 2019 (COVID-19) from standard-of-care chest …
prognostication of coronavirus disease 2019 (COVID-19) from standard-of-care chest …
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 infections. Rapid identification of COVID-19 and its severity in individual patients …
Two-step machine learning to diagnose and predict involvement of lungs in COVID-19 and pneumonia using CT radiomics
Objective To develop a two-step machine learning (ML) based model to diagnose and
predict involvement of lungs in COVID-19 and non COVID-19 pneumonia patients using CT …
predict involvement of lungs in COVID-19 and non COVID-19 pneumonia patients using CT …
High-dimensional multinomial multiclass severity scoring of COVID-19 pneumonia using CT radiomics features and machine learning algorithms
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 …
features to classify COVID-19 patients into severe-, moderate-, mild-, and non-pneumonic. A …
Changes in dietary patterns and clinical health outcomes in different countries during the SARS-CoV-2 pandemic
Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome
coronavirus 2 (SARS-CoV-2), has led to an excess in community mortality across the globe …
coronavirus 2 (SARS-CoV-2), has led to an excess in community mortality across the globe …
Development and validation of an automated radiomic CT signature for detecting COVID-19
J Guiot, A Vaidyanathan, L Deprez, F Zerka… - Diagnostics, 2020 - mdpi.com
The coronavirus disease 2019 (COVID-19) outbreak has reached pandemic status. Drastic
measures of social distancing are enforced in society and healthcare systems are being …
measures of social distancing are enforced in society and healthcare systems are being …
Diagnosis of COVID-19 using CT image radiomics features: a comprehensive machine learning study involving 26,307 patients
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 …
COVID-19 pneumonia from other lung diseases using a very large cohort of patients …
Screening of COVID-19 based on the extracted radiomics features from chest CT images
SM Rezaeijo, R Abedi-Firouzjah… - Journal of X-ray …, 2021 - content.iospress.com
METHODS: The study is carried out on two groups of patients, including 138 patients with
confirmed and 140 patients with suspected COVID-19. We focus on distinguishing …
confirmed and 140 patients with suspected COVID-19. We focus on distinguishing …
Machine learning and radiomics applications in esophageal cancers using non-invasive imaging methods—a critical review of literature
Simple Summary Non-invasive imaging modalities are commonly used in clinical practice.
Recently, the application of machine learning (ML) techniques has provided a new scope for …
Recently, the application of machine learning (ML) techniques has provided a new scope for …
[HTML][HTML] Multi-classifier-based identification of COVID-19 from chest computed tomography using generalizable and interpretable radiomics features
Purpose To investigate the efficacy of radiomics in diagnosing patients with coronavirus
disease (COVID-19) and other types of viral pneumonia with clinical symptoms and CT signs …
disease (COVID-19) and other types of viral pneumonia with clinical symptoms and CT signs …