European journal of radiology
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Multicenter Study
Deep learning-based multi-view fusion model for screening 2019 novel coronavirus pneumonia: A multicentre study.
To develop a deep learning-based method to assist radiologists to fast and accurately identify patients with COVID-19 by CT images. ⋯ Based on deep learning method, the proposed diagnosis model trained on multi-view images of chest CT images showed great potential to improve the efficacy of diagnosis and mitigate the heavy workload of radiologists for the initial screening of COVID-19 pneumonia.
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Multicenter Study
Radiomics nomogram for preoperative differentiation of lung tuberculoma from adenocarcinoma in solitary pulmonary solid nodule.
To investigate the preoperative differential diagnostic performance of a radiomics nomogram in tuberculous granuloma (TBG) and lung adenocarcinoma (LAC) appearing as solitary pulmonary solid nodules (SPSNs). ⋯ The radiomics nomogram we developed can preoperatively distinguish between LAC and TBG in patient with a SPSN.