Rad AI Launches with $4M, Will Use AI to Automate Administrative Radiology Tasks

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Radiologists face high error rates, burnout and rising imaging demand despite a shortage of specialists. And AI can help.

A newly launched company, Rad AI, plans to use its $4 million seed round to automate repetitive tasks for radiologists. The funding, led by Gradient Ventures, Google’s AI-focused venture fund, will also help the company expand its engineering team and the rollout of its product to more groups and customers.

Rad AI, founded by Jeff Chang, M.D., MBA, an emergency department radiologist at Greensboro Radiology in North Carolina, uses machine learning to automate tasks to give radiologists more time to focus on the accurate and timely diagnosis of patients.

“We help radiology groups significantly increase productivity, while reducing radiologist burnout and improving report accuracy,” said Chang. “By working closely with radiologists, we can make a positive impact on patient care.”

The technology generates the impression section of radiology reports and customizes it to the preferred language of the radiologist, Rad AI said.

The product has demonstrated an average of 20% time savings on the interpretation of CTs and 15% time savings on radiographs, which translates into an hour a day saved, the company claimed.

Customers have reported a reduction in burnout, error rates and turnaround time, resulting in improved radiologist well-being and patient care, claimed Rad AI.

“The team at Rad AI is uniquely suited to apply innovative technology to this field, with strong radiology and AI experts and firsthand knowledge of this market,” said Zachary Bratun-Glennon, J.D., MBA, partner at Gradient Ventures. “It’s exciting to see the quantitative benefits and positive feedback from (Rad AI’s) radiology customers, and we’re looking forward to the impact of (its) future products.”

Additional investments came from UP2398, Precursor Ventures, GMO Venture Partners, Array Ventures, Hike Ventures and Fifty Years VC.

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