Butterfly Network is integrating artificial intelligence with its portable ultrasound technology, and the outcomes are recorded in recent research published in the European Heart Journal. The study, conducted in collaboration with Tufts Medical Center, revealed that machine learning models adapted for Butterfly Network’s handheld iQ+ devices can identify aortic stenosis with 94% accuracy, as measured by AUROC scoring. This development addresses a critical healthcare gap, as over 13% of elderly Americans suffer from this often-undiagnosed valve condition that typically progresses unnoticed until severe symptoms emerge.

Butterfly Network simultaneously introduced an AI-enhanced training module within its Butterfly ScanLab platform, designed to teach medical professionals proper aortic scanning techniques through interactive iPad-based instruction featuring anatomical overlays and real-time feedback.

These parallel advancements in both diagnostic algorithms and clinician education create a comprehensive solution for early detection of cardiovascular abnormalities in non-specialist settings like primary care offices and long-term care facilities.

Image Credit: Butterfly Network