SINGAPORE, Oct. 15, 2020 /PRNewswire/ -- See-Mode Technologies, a MedTech startup based in Singapore and Australia that seeks to empower clinicians to better predict stroke, today announced that it has received 510(k) clearance from the U.S. Food and Drug Administration (FDA) for its debut product, Augmented Vascular Analysis (AVA), a world-first medical Artificial Intelligence (AI) software for automated analysis and reporting of vascular ultrasound scans.
AVA uses deep learning, text recognition, and signal processing technologies to assist clinicians in interpreting and reporting vascular ultrasound studies – typically a manual and error-prone process. With a single click and in less than a minute, AVA can analyse a full vascular ultrasound scan, minimising the need for manual drawings. By significantly reducing the time taken to analyse images and generate reports, See-Mode's AVA augments the clinical workflow, resulting in greater overall productivity, accuracy and improved patient outcomes.
"Receiving our first FDA clearance is a huge step for us at See-Mode, which demonstrates the strength of the product we have built and the robustness of our approach in running clinical studies," said Dr Milad Mohammadzadeh, Co-Founder and Director, See-Mode Technologies. "We are extremely thankful to the outstanding group of clinicians who have worked closely with us to validate our models and build clinical evidence for the regulatory approval of AVA and our future products. Riding on this momentum, we will be ramping up our plans to bring AVA to the U.S. market within the year, to enable clinicians across the U.S. to do their work more efficiently and analyse medical images with a greater control on quality."
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Despite being a highly-preventable disease, stroke remains a leading cause of death and disability around the world. To help clinicians better predict the risk of stroke and vascular diseases, See-Mode is developing novel solutions to improve the analysis of routinely collected medical images such as ultrasound, CT or MRI scans. By applying AI and computational models on these medical images, clinicians are able to obtain stroke risk factors that may not be accessible in current clinical practice.
Aside from AVA, See-Mode has been building two other new products - to detect vulnerable plaque using machine learning and to identify high-risk blood flow using computational modelling. The startup has completed strong proof-of-concepts for both products with collaborators in Singapore and Australia, and multi-centre clinical studies are now being conducted with partners across Europe and the United States.