aceArtificial Intelligence in Cerebral Small Vessel Disease Imaging: A Study-Level Cross-Sectional Analysis of Validation Status and Clinical Applicability
Artificial intelligence (AI) is increasingly used in cerebral small vessel disease (CSVD) imaging, but the extent of validation and clinical applicability across the literature remains uncertain. We performed a study-level cross-sectional analysis using a frozen Web of Science Core Collection (WoSCC) cohort supplemented by PubMed and IEEE Xplore searches to assess database coverage and the stability of findings from the WoSCC cohort. After study-level reconciliation, 463 independent studies were included. White…
Artificial Intelligence in Cerebral Small Vessel Disease Imaging: A Study-Level Cross-Sectional Analysis of Validation Status and Clinical Applicability: White matter hyperintensity segmentation/quantification was the most common task (196/463, 42.3%), followed by cerebral microbleed detection/classification (82/463, 17.7%), perivascular space/lacune assessment (67/463, 14.5%), CSVD burden/risk modeling (62/463, 13.4%), and clinical outcome prediction (56/463, 12.1%).
Evidence
- Peer-reviewedJournal of Imaging Informatics in Medicine2026-09-18
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Truvace Impact Record TRV-2026-1149, v2: “Artificial Intelligence in Cerebral Small Vessel Disease Imaging: A Study-Level Cross-Sectional Analysis of Validation Status and Clinical Applicability.” Truvace, 2026-10-26. /record/TRV-2026-1149 (accessed at citation time). sha256 5924e91f7cfa773a…
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