Butterfly Network Inc. is touting its role in new research demonstrating the potential for machine learning (ML) models to support early aortic stenosis (AS) detection using handheld ultrasound devices.

A study conducted by Tufts Medical Center and published in European Heart Journal – Imaging Methods and Practice, demonstrates that a ML model fine-tuned for use on Butterfly iQ+ devices is highly accurate in identifying AS. The findings support the value of ML model development, and ultimately, are a positive step toward portable screening for earlier AS detection, according to the company.

Aortic stenosis, or aortic valve narrowing, affects more than 13% of Americans older than 75 and is often missed until it’s advanced and symptomatic. Studies suggest a significant number of AS cases remain undiagnosed, particularly among underserved and aging populations. This delay in diagnosis is associated with higher risk procedures, worse outcomes, and increased healthcare costs. As earlier identification and AS treatments are increasingly associated with better patient outcomes, the need for upstream, accessible screening is critical.

“This research shows a promising path forward where lower-level providers, not just cardiologists or trained sonographers, could screen for aortic stenosis using AI-assisted handheld ultrasound,” study co-author and Butterfly Network Chief Medical Officer Emeritus Dr. John Martin said. “This opens the door to early detection in a wide variety of care venues including primary care offices, long term care facilities, urgent care facilities and even in the home.”

The study validated that an ML model trained on hospital-grade ultrasound images performed well when adapted to Butterfly’s handheld ultrasound device. After fine-tuning the final layer of a neural network, researchers achieved an area under the receiver operator characteristic curve (AUROC) of 0.94 for differentiating between no aortic stenosis and any degree of aortic stenosis on handheld ultrasound images—a level of accuracy that supports potential clinical use in screening workflows.

In a related development, Butterfly has recently released the latest expansion of its Butterfly ScanLab AI-powered ultrasound education app: an Aorta Exam Protocol. This educational app harnesses animations, anatomical labeling, and a quality indicator to help teach users how to scan the abdominal aorta and recognize normal anatomy. With that training, users can then use POCUS to detect life-threatening conditions like abdominal aortic aneurysms (AAA) and dissections. Designed for ease of use on an iPad, the module is included in every Butterfly membership and compatible with existing Butterfly probes.

“Early detection saves lives, but access to imaging remains a major barrier. Butterfly Network President/ CEO/Chairman Joseph DeVivo stated. “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 is attempting to drive a digital revolution in medical imaging with its proprietary Ultrasound-on-Chip semiconductor technology and ultrasound software solutions. In 2018, Butterfly Network launched the world’s first handheld, single-probe, whole-body ultrasound system, Butterfly iQ. The iQ+ followed in 2020, and the iQ3 in 2024, each with improved processing power and performance by leveraging Moore’s Law. The iQ3 earned Best Medical Technology at the 2024 Prix Galien USA Awards, an honor and one of the highest accolades in healthcare. Butterfly’s innovations have also been recognized by Fierce 50, TIME’s Best Inventions and Fast Company’s World Changing Ideas, among other achievements.

Butterfly combines advanced hardware, intelligent software, AI, services, and education to drive adoption of affordable, accessible imaging. Clinical publications demonstrate its handheld ultrasound probes paired with Compass enterprise workflow software can help hospital systems improve care workflows, reduce costs, and enhance provider economics. With a cloud-based solution that enables care anywhere through next-generation mobility, Butterfly aims to democratize healthcare by addressing critical global healthcare challenges. Butterfly devices are commercially available to trained healthcare practitioners in parts of Africa, Asia, Australia, Europe, the Middle East, North America and South America, among other areas.