Los Angeles-based iCardio.ai has received FDA 510(k) clearance for its artificial intelligence software for interpretation of echocardiography, aimed at offering a comprehensive imaging workflow and autonomous preliminary reporting.

iCardio.ai develops machine learning and deep learning algorithms for the examination of ultrasound applications with a particular focus on transthoracic echo. 

In a statement, the company said it has started mobilizing its commercial operations with integrations in several partner systems.

EchoMeasure is iCardio.ai's first FDA-cleared software, which supports a strong reading workflow for automated echocardiographic interpretation.

The FDA clearance for the system is designed to act as the foundation on which the company's future algorithms will be supported, specifically the structural heart disease detection algorithm suite.

In addition, a few of the algorithms can be used to detect valvular heart disease and, according to the company, has attracted attention from health systems and prosthetic valve manufacturers. 

The company says the predicted revenue will be used to drive future initiatives. 

THE LARGER TREND

In September, iCardio.ai collaborated with Abbott to develop AI applications for its imaging devices. 

iCardio.ai will support Abbott's strategy of automating model creation on the company's EnSiteX cardiac mapping system utilizing 2D intracardiac echo (ICE) images that are captured by Abbott's ICE catheters.

The same month, iCardio.ai joined the 10th cohort of the Cedars-Sinai Accelerator. Participants in the accelerator program received personalized guidance, support and exposure to a wide network of healthcare entrepreneurs, investors and advisors to help them navigate companies' healthcare offerings. 

Also in September, iCardio.ai partnered with SAR MedIQ to accelerate the availability of AI in cloud PACS and the broader cardiology healthcare industry. The alliance will provide insights into echocardiography quality and introduce efficiencies designed to alter how ultrasound images are assessed and diagnosed.