In 2017, Vinod Khosla told CNBC that “the radiologist’s work will be obsolete in five years”. Although the founder of Khosla Ventures later revised this schedule for up to 15 yearshe claimed that AI image recognition could soon diagnose diseases on scans better than human doctors.
Seven years later, radiologists are still required to interpret most scans (even though AI software helps them); The most immediate challenge is the shortage of these doctors in U.S It is around the world.
While Khosla Ventures has backed several imaging startups, including Vista.ai It is Q BiographyThe firm’s latest bet is on a company that eases radiologists’ workload, reducing the time spent documenting reports, instead of trying to replace the doctor with a machine.
On Tuesday, Khosla led a $50 million Series B in Rad AI, which has developed a tool that can generate reports for radiologists. Other participants in the round included World Innovation Lab and returning investors ARTIS Ventures, OCV Partners, Kickstart Fund and Gradient Ventures (Google’s AI-focused fund). The financing brought the company’s total capital to more than US$80 million.
Rad AI was founded in 2018 by Dr. Jeff Chang, who completed his medical training as a radiologist at age 16 and later received an MBA from UCLA, and serial entrepreneur Doktor Gurson.
Because Chang knew from his own experience as a physician that most of radiologists’ time is spent documenting findings rather than analyzing images, the pair decided to develop a proprietary LLM trained on radiology report datasets to automate documentation of findings and doctors’ impressions.
Although technology companies didn’t widely use generative AI until OpenAI’s ChatGPT arrived on the scene in 2022, Rad AI is proud to be an early adopter of this technology. “I’m confident we’re the first company in radiology to start using LLMs,” Gurson, CEO of Rad AI, told TechCrunch. “We started doing this work in 2018, around the same time that open AI was creating its [first] models.”
Six years later, Rad AI’s products are used by about a third of U.S. health systems and nine of the country’s 10 largest radiology groups, Gurson said.
The new capital will be used to build a team that will deploy Rad AI’s latest product: an autonomous radiology reporting solution.
“We have a lot of interest, but there is a limit to what we can deploy at once,” Gurson said, adding that Rad AI is hiring people who can install and maintain the software.
Some incumbents have been trying to add GenAI functionality to their radiology reporting software over the past 18 months, but Rad AI does not yet consider these companies to be true competitors.
“At this point, probably 99% to 100% of the market uses our products,” he said. “If there’s any indication, we haven’t lost a single customer since we started.”
