Bay Labs has raised $5.5 million to propel its artificial intelligence system for cardiovascular images toward the market. The technology is designed to support the performance and interpretation of echocardiograms, expanding the pool of physicians who can diagnose cardiovascular disease.
San Francisco, Calif.-based Bay Labs has tapped into the growing number of tech VCs with an interest in healthcare to bankroll its development. Existing investor Khosla Ventures led the series A round with assists from Data Collective (DCVC), Greenbox Venture Partners, Minneapolis Heart Institute Ventures and early Google employee Georges Harik.
The experimental technology in development at Bay Labs draws on resources including a library of 40 million videos to help healthcare professionals perform and interpret cardiovascular ultrasound scans. This support spans from input to helping the operator position the probe correctly to the automation of calculations including heart valve dimensions and the volume of blood pumped.
Bay Labs’ backers think its focus on ultrasound and AI puts it at an intersection with big potential.
“Medical devices could see tremendous benefits from applying AI because they are static devices that produce hard-to-read data, which requires significant interpretation time from specialists,” Armen Vidian, DCVC operating partner, wrote in a blog post. “Ultrasound ... presents an ideal application for deep learning ... because of the high volume of nuanced structural information produced in every reading.”
Bay Labs is working with people at organizations including Minneapolis Heart Institute, Northwestern Medicine, Duke University School of Medicine and Stanford University to turn this idea into a commercial product. The series A positions Bay Labs to continue this validatory work.