In 2017, Vinod Khosla told CNBC that the job “of the radiologist will be obsolete in five years.” While the founder of Khosla Ventures later revised that timeline to as long as 15 years, he maintained that AI image recognition could soon diagnose disease on scans better than human doctors.
Seven years later, radiologists are still required to interpret most scans (even if AI software helps them); the more immediate challenge is the shortage of these doctors in the United States and around the world.
While Khosla Ventures has backed several imaging startups, including Vista.ai and Q Bio, the firm’s latest bet is on a company that makes radiologists’ workload easier by reducing the time spent on report documentation, instead of trying to replace the physician with a machine.
On Tuesday, Khosla led a $50 million Series B into Rad AI, which 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 raised to over $80 million.
Rad AI was founded in 2018 by Dr. Jeff Chang, who completed his medical training as a radiologist when he was 16 and later received an MBA from UCLA, and serial entrepreneur Doktor Gurson.
Since Chang knew from his own experience as a practicing doctor that the majority of radiologists’ time is spent documenting findings rather than analyzing images, the pair decided to develop a proprietary LLM trained on radiology report datasets for automating doctors’ findings and impressions documentation.
While tech companies didn’t widely use generative AI until OpenAI’s ChatGPT burst onto the scene in 2022, Rad AI takes pride in being an early adopter of this technology. “I’m confident we’re the first company in radiology to start using LLMs,” Gurson, Rad AI’s CEO told TechCrunch. “We started doing that work in 2018, around the same time that open AI was creating their [first] models.”
Six years later, Rad AI’s products are used by about a third of U.S. health systems and nine of the ten largest radiology groups in the country, Gurson said.
The fresh capital will be used to build a team that deploys Rad AI’s latest product: a standalone radiology reporting solution.
“We have a lot of interest, but there’s only so much 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 doesn’t consider these companies to be true competitors yet.
“At this point, probably 99% to 100% of the market uses our products,” he said. “If it’s any indication, we’ve not lost a single customer since we started.”
