Diagnostic Accuracy of Artificial Intelligence in Detecting Pleural Effusion on Ultrasound Imaging: A Systematic Review and Meta‐Analysis
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.
Authors
- Teck Yon Lee
- Sophia Wong Ching Hwai
Institutions
- NHS Fife (GB)
- Northern Health and Social Care Trust (GB)
Publication Details
- Journal
- Journal of Clinical Ultrasound
- Published
- 2026-01-08
- DOI
- https://doi.org/10.1002/jcu.70168
- Primary Topic
- Ultrasound in Clinical Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00