Diagnostic Accuracy of Artificial Intelligence in Detecting Pleural Effusion on Ultrasound Imaging: A Systematic Review and Meta-Analysis.
Authors
Affiliations (2)
Affiliations (2)
- NHS Fife, Kirkcaldy, UK.
- Northern Care Alliance NHS Foundation Trust, Greater Manchester, UK.
Abstract
Artificial intelligence (AI) interpretation of ultrasound (US) images is promising, yet its accuracy in diagnosing pleural effusions remains unclear. We conducted a comprehensive database search which identified 84 studies, of which 6 met eligibility criteria. We included 2951 patients with 58 392 images and 12 069 ultrasound clips. Bivariate analysis revealed a pooled sensitivity of 0.92 (95% CI: 0.85-0.96, p < 0.05) and specificity of 0.96 (95% CI: 0.88-0.99, p < 0.05), with a high AUC of 0.98 under the sROC curve, although included studies had significant heterogeneity, I<sup>2</sup> > 99%. AI demonstrates high diagnostic accuracy in detecting pleural effusion on ultrasound.