Butterfly Network has made significant progress in advancing AI-powered screening for aortic valve and aorta conditions, unveiling new research and training tools designed to enhance diagnostic accuracy and accessibility. The company’s latest developments leverage artificial intelligence to improve the detection of critical cardiovascular issues, particularly in underserved or resource-limited settings. By integrating AI into its handheld ultrasound platform, Butterfly Network aims to empower healthcare providers with real-time, actionable insights during routine screenings. The newly released tools include enhanced algorithms trained on diverse clinical datasets, enabling more reliable identification of aortic stenosis, aneurysms, and other structural heart abnormalities. These innovations are supported by peer-reviewed research demonstrating improved sensitivity and specificity compared to traditional methods. The company also introduced interactive training modules to help clinicians interpret AI-generated findings, reducing the learning curve and increasing confidence in early diagnosis. With a focus on democratizing access to advanced cardiac imaging, Butterfly Network’s advancements represent a major step forward in preventive cardiology and point-of-care diagnostics.

Butterfly Network, Inc. (NYSE: BFLY) has announced significant advancements in AI-powered ultrasound technology, highlighting its role in groundbreaking research on early detection of aortic stenosis (AS) using handheld devices. In collaboration with Tufts Medical Center, the company contributed to a study published in the European Heart Journal – Imaging Methods and Practice, demonstrating that a machine learning (ML) model fine-tuned for Butterfly iQ+ devices can accurately identify AS with high precision. The model achieved an area under the receiver operating characteristic curve (AUROC) of 0.94—indicating strong performance—when distinguishing between no aortic stenosis and any degree of the condition using handheld ultrasound images. Aortic stenosis, a narrowing of the aortic valve, affects over 13% of Americans aged 75 and older and is frequently undiagnosed until symptoms become severe. This delay leads to higher-risk procedures, poorer outcomes, and increased healthcare costs. Early detection is crucial for better patient results, yet access to imaging remains a major barrier, especially in underserved and aging populations. The new study suggests that AI-assisted handheld ultrasound could enable earlier screening by non-specialist providers, such as primary care physicians, nurses, and even patients at home, in settings like clinics, long-term care facilities, and urgent care centers. The ML model was initially trained on hospital-grade ultrasound data but was successfully adapted to Butterfly’s portable iQ+ device through fine-tuning the final layer of a neural network. This adaptation demonstrates the potential for AI to bridge the gap between high-quality imaging and accessible, point-of-care diagnostics. The findings support the broader vision of integrating AI into handheld ultrasound systems to expand diagnostic capabilities beyond traditional imaging centers. In parallel, Butterfly has expanded its Butterfly ScanLab™ AI-powered education app with a new Aorta Exam Protocol. This interactive module uses animations, anatomical labeling, and real-time quality feedback to teach users how to perform abdominal aortic scans and identify normal anatomy. It is designed for use on iPads and is included in all Butterfly memberships, making it accessible to healthcare providers using existing Butterfly probes. The tool aims to improve scanning accuracy and confidence, enabling earlier detection of life-threatening conditions such as abdominal aortic aneurysms (AAA) and dissections. Joseph DeVivo, President, CEO, and Chairman of Butterfly Network, emphasized the transformative potential of combining AI and education: “Early detection saves lives, but access to imaging remains a major barrier. This work is about democratizing diagnostics. With AI and education working hand in hand, we’re empowering more providers to deliver proactive care in places that were never possible before.” Butterfly Network continues to lead in digital health innovation with its Ultrasound-on-Chip™ technology. The company launched the world’s first handheld, single-probe, whole-body ultrasound system, Butterfly iQ, in 2018, followed by the iQ+ in 2020 and the iQ3 in 2024—recognized with the 2024 Prix Galien USA Award for Best Medical Technology. The iQ3 also earned accolades from TIME’s Best Inventions and Fast Company’s World Changing Ideas. Butterfly’s integrated platform combines advanced hardware, AI, cloud-based software, and educational tools to improve care workflows, reduce costs, and enhance provider efficiency. The company’s devices are commercially available in numerous countries across North America, Europe, Asia, Africa, and the Middle East, supporting global efforts to expand access to affordable, high-quality medical imaging. This research and product development underscore Butterfly’s mission to democratize healthcare by making advanced diagnostics accessible, affordable, and usable by a broader range of providers and patients.