Radiomics-based model for accurately distinguishing between severe acute respiratory syndrome associated coronavirus 2 (SARS-CoV-2) and influenza A infected pneumonia.

ABSTRACT: Clinicians have been faced with the challenge of differentiating between severe acute respiratory syndrome associated coronavirus 2 (SARS-CoV-2) infected pneumonia (NCP) and influenza A infected pneumonia (IAP), a seasonal disease that coincided with the outbreak. We aim to develop a machine-learning algorithm based on radiomics to distinguish NCP from IAP by texture analysis based on computed tomography (CT) imaging. Forty-one NCP and 37 IAP patients admitted from January to February 6, 2019 admitted to two hospitals in Wenzhou, China. All patients had undergone chest CT examination and blood routine tests prior to receiving medical treatment. NCP was diagnosed by real-time RT-PCR assays. Eight of 56 radiomic features extracted by LIFEx were selected by least absolute shrinkage and select

SUBMITTER: Zeng QQ 

PROVIDER: S-EPMC7436469 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature