Clinician-reviewed AI-guided scans were rapid, sensitive for DVT, and specific for prioritizing patients requiring standard of care ultrasounds, suggesting AI-guided ultrasound may be a scalable triage strategy to expand DVT evaluation access, particularly in resource-constrained and after-hours settings.
It is demonstrated that the hybrid AI-human model achieved high diagnostic performance for ruling out proximal DVT, with a sensitivity of 90-100% and a negative predictive value (NVP) of 87.5-100%.
Syed Zulfiqar Ali Shah, Muhammad Kaleem Akhtar, Waqar Ahmad et al.· Veredas do Direito· 0 citations
AI should be viewed not as a replacement for ultrasound professionals but as a decision-support technology that may improve consistency, efficiency, and diagnostic confidence when carefully validated in real-world clinical settings.
Bayan Alghamdi, Eman M Alrewily, Sharefa S Alghamdi· Ultrasound Quarterly· 0 citations
A deep learning algorithm accurately detected moderate or greater AS across validation cohorts in this study and support a scalable strategy that may expand access to AS detection in settings with limited echocardiography resources.
Eunjung Lee, J. Naser, Conor J. Kane et al.· JAMA cardiology· 1 citation
The development of AI systems to support LUS interpretation shows high potential; however, current studies exhibit significant heterogeneity in their objectives, methodologies, and evaluation metrics.
Julia López-Canay, Alberto Fernández-Villar, Cristina Ramos-Hernández et al.· Frontiers in Radiology· 1 citation
Artificial intelligence (AI) is increasingly used in echocardiography and point-of-care ultrasound (POCUS) to support image acquisition, view recognition, image-quality assessment, segmentation, automated quantification, disease classification, reporting, and bedside decision support. This narrative review summarizes c...
F. Savorgnan, Pranathi Pilla, Sarah Visokay et al.· Current Pediatrics Reports· 0 citations
Evidence indicates that ultrasound-based radiomics and AI enhance plaque characterization, automate segmentation, and support risk stratification in carotid artery disease, peripheral arterial disease, venous thromboembolism, and abdominal aortic aneurysms.
A. W. Islam, N. Tariq, Subair Sabbar Ahmed· Journal for Vascular Ultraso...· 0 citations
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