AI-enabled imaging company Aidoc scooped up $110 million in a Series D funding round.
The round was led by TCV and Alpha Intelligence Capital with participation from AIC’s co-investor CDIB Capital. The investment, which comes nearly a year after the startup announced its $66 million Series C, brings Aidoc’s funding pot to $250 million.
WHAT IT DOES
Aidoc offers tools that help radiologists find and triage injuries and health conditions based on imaging results. It also provides coordination software for stroke and cardiovascular care, alerting relevant members of the care team and sharing data and images.
The startup has received a slew of FDA 510(k) clearances, including for software aimed at finding and triaging potential brain aneurysms in CT scans and flagging pneumothorax, or a collapsed lung, on X-rays.
Aidoc said the Series D investment will fund the expansion of its AI Care Platform, which includes its identification and triage tools, as well as its care coordination software.
“We are building the kind of breadth and depth in AI that is allowing hospitals to fundamentally change the way they do business and provide the solutions needed to successfully compete during these challenging times,” CEO Elad Walach said in a statement.
“… With this new round of investment, our aim is to massively ramp up our AI Care Platform to cover both the various hospital medical service lines and the depth of integration into the clinical workflows, empowering hospitals to activate cross-specialty care teams and deliver the best quality of care in a scalable, efficient way to patients.”
Aidoc isn’t alone in AI-powered radiology. RapidAI recently received FDA clearance for a product that identifies potential cases of central pulmonary embolism and alerts providers.
In March, French company Gleamer announced a 510(k) for its tool, which aims to find fractures in X-rays. The company recently partnered with Aidoc to integrate the BoneView software into Aidoc’s platform. Others in the space include Nanox, Qure.ai and Viz.ai.
Recent studies published in the Lancet Digital Health raised some concerns about AI and imaging. One study found an algorithm used to detect hip fractures outperformed human radiologists, but also noted some barriers that would prevent safe use, like the occasional unexpected error a human wouldn’t make.
Another study found that a deep learning model could predict race from imaging results, which researchers were concerned could perpetuate health disparities.