An AI tool using echocardiograms accurately screens for cardiac amyloidosis, outperforming traditional detection methods.
Key Details
- 1AI model analyzes echocardiogram (ultrasound) images to screen for cardiac amyloidosis.
- 2Developed by Mayo Clinic and Ultromics; validated in a global, multi-ethnic cohort across 18 hospitals.
- 3Achieved 85% sensitivity and 93% specificity in detecting or ruling out cardiac amyloidosis.
- 4Outperformed existing clinical scoring systems for early diagnosis.
- 5FDA-cleared and already being implemented in multiple US hospitals.
Why It Matters
Early, accurate identification of cardiac amyloidosis is critical due to effective therapies available only at earlier disease stages. AI-based screening of routine cardiac ultrasound could substantially improve detection rates and patient outcomes, supporting broader integration of imaging AI in clinical care.

Source
EurekAlert
Related News

•EurekAlert
BraDiPho: New 3D AI Atlas Integrates Brain Dissections with MRI
Researchers have developed BraDiPho, a tool that merges ex-vivo photogrammetric brain dissection data with in-vivo MRI tractography using AI.

•EurekAlert
AI Maps Genetic Factors Shaping the Corpus Callosum via MRI Scans
USC researchers used AI to analyze MRI scans and uncover the genetic architecture of the brain's corpus callosum.

•EurekAlert
WashU Launches AI Imaging Center to Advance Precision Diagnostics
Washington University establishes a new center to develop AI-powered imaging tools for better diagnosis and precision medicine.