A deep learning model using echocardiography accurately detects cardiac amyloidosis, outperforming traditional methods.
Key Details
- 1AI model trained on echocardiography video clips from 2,612 patients across multiple sites and ethnic groups.
- 2External validation performed on 18 global sites; included 597 amyloidosis cases and 2,122 controls.
- 3Achieved AUROC of 0.93 (after excluding 13% uncertain predictions), sensitivity of 85%, specificity of 93%.
- 4Performance was consistent across amyloidosis subtypes and various subgroups.
- 5The AI model outperformed transthyretin cardiac amyloidosis (TTR-CA) score (AUROC = 0.73) and wall thickness scoring (AUROC = 0.8).
- 6Ultromics employees contributed and funded the study.
Why It Matters

Source
AuntMinnie
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