A Meta-Analysis of Computerized Tomography-Based Radiomics for the Diagnosis of COVID-19 and Viral Pneumonia.
Yung-Shuo KaoKun-Te LinPublished in: Diagnostics (Basel, Switzerland) (2021)
A total of 10,300 patients were involved in this meta-analysis. The radiomics quality score ranged from 13 to 16 (maximum score: 36). The pooled sensitivity was 0.885 (95% CI: 0.818-0.929), and the pooled specificity was 0.811 (95% CI: 0.667-0.902). The pooled AUC was 906. Conclusion: Our meta-analysis showed that CT-based radiomics feature models can successfully differentiate COVID-19 from other viral pneumonias.
Keyphrases
- sars cov
- systematic review
- coronavirus disease
- contrast enhanced
- lymph node metastasis
- end stage renal disease
- meta analyses
- ejection fraction
- chronic kidney disease
- newly diagnosed
- computed tomography
- respiratory syndrome coronavirus
- prognostic factors
- case control
- clinical trial
- deep learning
- patient reported outcomes
- study protocol
- acute respiratory distress syndrome