Aortic stenosis
Disease1 paper1 finding
- In silico1
Associations
1Deep learning algorithm
upin silico1
1 study
Deep learning algorithm
upin silico1
deep learning algorithm predicts aortic stenosis in silico (sensitivity 0.92, specificity 0.98).
In silicomoderate-to-severe ASnongated, noncontrast chest CTn = 239
Deep learning matches experts in scoring aortic valve calcium · JACC. Advances · 23 Sep 2026
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3Deep learning matches experts in scoring aortic valve calcium
Algorithm scores correlated strongly with expert assessments at r = 0.99, identifying moderate-to-severe aortic stenosis with 0.92 sensitivity and…Algorithm scores correlated strongly with expert assessments at r = 0.99, identifying moderate-to-severe aortic stenosis with 0.92 sensitivity and 0.98 specificity.
ASXL1 mutations in clonal hematopoiesis accelerate aortic valve calcification
Large human cohort data and cell experiments show that ASXL1-driven clonal hematopoiesis worsens aortic valve hemodynamics and promotes calcification…Large human cohort data and cell experiments show that ASXL1-driven clonal hematopoiesis worsens aortic valve hemodynamics and promotes calcification through inflammatory signaling.