Radiomics analysis for distinctive identification of COVID-19 pulmonary nodules from other benign and malignant counterparts

Radiomics analysis for distinctive identification of COVID-19 pulmonary nodules from other benign and malignant counterparts

Abstract This observational study investigated the potential of radiomics as a non-invasive adjunct to CT in distinguishing COVID-19 lung nodules from other benign and malignant lung nodules. Lesion segmentation, feature extraction, and machine learning algorithms, including decision tree, support v...

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Bibliographic Details
Main Authors: Minmini Selvam, Anupama Chandrasekharan, Abjasree Sadanandan, Vikas K. Anand, Sidharth Ramesh, Arunan Murali, Ganapathy Krishnamurthi
Format: Article
Language:English
Published: Nature Portfolio 2024-03-01
Series:Scientific Reports
Subjects:
Radiomics
Lung
Nodules
COVID-19
Machine learning
Classifiers
Online Access:https://doi.org/10.1038/s41598-024-57899-x

Internet

https://doi.org/10.1038/s41598-024-57899-x

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