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
AI and Imaging Reveal Atomic Order in 2D Nanomaterials
A multi-university team has uncovered how atomic order and disorder in 2D MXene nanomaterials can be predicted and tailored using AI, enabled by advanced imaging analysis.
•EurekAlert
DreamConnect AI Translates and Edits fMRI Brain Activity into Images
Researchers unveil DreamConnect, an AI system that reconstructs and edits visual imagery from fMRI brain data with language prompts.
•EurekAlert
AI-Powered Optical Imaging Achieves High Accuracy for Colorectal Cancer Detection
A label-free optical imaging technique using autofluorescence lifetime and AI can distinguish colorectal cancer with 85% accuracy.