Rethinking Peripheral Artery Disease Screening with AI

*Investigational Study*

Peripheral Artery Disease (PAD) affects over 200 million people worldwide. It is one of the leading causes of limb loss and can lead to functional disabilities, chronic wounds, and mortality in late stages. Early screening, detection, and prevention is key to managing PAD.

Awareness among primary care providers Is low and access to specialists Is limited, particularly in communities where amputation rates are highest. The ankle-brachial index (ABI) is a widely used non-invasive test for PAD. However, it has various limitations including the inability to screen those with calcified non-compressible tibial vessels.

AutoABI is a smartphone-based tool which predicts a clinically significant ABI range from the doppler sound within seconds using advancements in AI-based sound analysis.

Simplified ABIs directly from doppler sounds

  1. Find a hand-held doppler device

  2. Listen to one of the ankle arteries (Dorsalis Pedis or Posterior Tibial)

  3. Tap "Start Analysis" in the AutoABI mobile app

  4. The ABI range result will pop-up within seconds

  5. AutoABI also detects interference and the presence of background noises to prevent mispredictions

How AutoABI aims to improve PAD diagnosis

📱 Accessibility of ABIs

Enabling ABI range predictions directly from hand-held dopplers without the need for expensive doppler ultrasound machinery

🫀 ABIs in Non-Compressible Vessels

Enabling ABI measurements in non-compressible tibial vessels where current methods are unable to

⌚️ More Efficient ABIs

ABIs within seconds can allow for more patients to be screened in a certain amount of time

Powered by artificial intelligence

AutoABI enables the prediction of ABI ranges directly from doppler sounds using state-of-the-art artificial intelligence algorithms. AutoABI is powered by a neural network capable of classifying ABIs from sound with high accuracy.

Undergoing clinical trials

AutoABI is undergoing clinical validation in a multi-site IRB-approved clinical study at Stanford University. The app is deployed to TestFlight where various vascular technicians are using it. Before deploying AutoABI to the App Store, we are prioritizing an in-depth validation of our algorithm to ensure a high level of accuracy and usability.