Rad AI secures $50 million to expand the utilization of generative AI technology among radiologists.

Rad AI, a startup specializing in AI technology for radiology, raised $50 million in new funding to broaden the global reach of its generative AI solutions. The Series B round was led by Khosla Ventures, with contributions from WiL (World Innovation Lab) and existing investors including Artis Ventures, OCV Partners, Kickstart Fund, and Gradient Ventures (Google's AI-focused fund). This brings the total raised by the company to over $80 million.

The most recent funding round will expedite the advancement and global deployment of the company's products as Rad AI enlarges its workforce, the company announced.

Rad AI devised technology aimed at streamlining the workload of radiologists by reducing the time spent on report documentation. Radiologists reportedly allocate 75% of their time to dictating reports based on medical images, often generating reports for over 100 patients daily.

According to the company, its solutions are currently utilized by more than a third of all U.S. health systems and by nine out of the 10 largest U.S. radiology practices. Founder Jeff Chang, M.D., a radiologist, initiated the company due to concerns about high error rates, radiologist burnout, and increasing imaging demand amidst a growing shortage of U.S. radiologists. Rad AI utilizes cutting-edge machine learning and AI to automate repetitive tasks for radiologists and streamline workflow for health systems. It has the capability to generate segments of the radiology report tailored to the radiologist's language and style.

Doktor Gurson, co-founder and CEO at Rad AI, stated, "At Rad AI, we've developed the most widely adopted generative AI solutions in healthcare, saving physicians time and enhancing patient care." He added, "Rad AI has become an integral part of health system workflows over the past five years. This strategic funding round further solidifies our position as the leading AI-driven workflow platform in healthcare."

The company's Rad AI Reporting serves as an AI-enhanced solution for radiology reporting workflow, and it has also created a patient follow-up solution known as Rad AI Continuity.

Earlier this year, Rad AI collaborated with Google to leverage its cloud infrastructure and advanced language models to streamline workflows and alleviate administrative burdens for radiologists. Through this partnership, Rad AI will utilize Google's cloud platform and AI tools, including MedLM, tailored for healthcare industry applications, including future Gemini-based models.

Rad AI asserts that health systems adopting its solutions witness a significant rise in patient follow-up rates for actionable findings, from 30% to over 85%, facilitating prompt diagnosis and treatment of new cancers. Additionally, health system clients can produce reports twice as quickly while reducing the number of dictated words, in many instances by up to 90%, potentially mitigating radiologist fatigue and burnout. The technology also purportedly slashes report error rates by nearly 50% for complex cases, thereby enhancing the quality of care.

With over 80% of healthcare data originating from radiology, Rad AI has access to an extensive repository of data to train its proprietary Large Language Models (LLMs). The company claims its models are trained on some of the largest healthcare datasets globally, including exclusive collaborations with numerous leading health systems and radiology practices.

Alex Morgan, M.D., Ph.D., a partner at Khosla Ventures, commented, "Rad AI's revolutionary reporting software—empowered by their proprietary LLMs trained on some of the world's largest radiology datasets—substantially reduces the time radiologists spend on their workload while alleviating fatigue and burnout."

Source: Fierce Healthcare