What You Should Know:
– Rad AI, a Berkely, CA-based radiologist-led AI company, today announced $25M in Series A funding led by ARTIS Ventures with participation by several existing investors, including OCV Partners, Kickstart Fund, and Gradient Ventures (Google’s AI-focused fund).
– Rad AI Omni automatically generates a customized impression from the findings and clinical indication dictated by the radiologist, using the most advanced neural networks. It learns each radiologist’s language preferences from all of their prior reports, to create an impression that the radiologist can simply review and finalize.
Designed by Radiologists, for Radiologists
Rad AI was founded by radiologists who understand these pressures firsthand. Founder Dr. Jeff Chang, the youngest radiologist and second youngest doctor on record in the US, was troubled by high error rates, radiologist burnout, and rising imaging demand despite a worsening shortage of US radiologists, so he decided to pursue graduate work in machine learning to identify ways that AI could help. After he met serial entrepreneur Doktor Gurson, they created Rad AI in 2018 at the intersection of radiology and AI. Built by radiologists, for radiologists, Rad AI is transforming the field of radiology with the inside perspective as its driving force.
Rad AI uses state-of-the-art machine learning to streamline repetitive tasks for radiologists, which yields substantial time savings, alleviates burnout, and creates more time to focus on patient care. Its first product, Rad AI Omni, saves radiologists an average of 60 minutes per day, and helps achieve up to 20% time savings per report.
In addition, Rad AI Omni improves report accuracy and consistency by making sure to include significant incidental findings, answering the main clinical question, and providing consensus guideline recommendations for follow-up. The impression appears in the practice’s voice recognition software as soon as the radiologist finishes dictating the findings, without any clicks, hotkeys or new windows.
Rad AI’s second product, Continuity, closes the loop on follow-up recommendations for significant incidental findings in radiology reports. Using AI-driven automation, Continuity ensures that appropriate patient follow-up is communicated and completed. This improves patient outcomes, reduces health system liability, and drives new financial value for health systems and radiology practices. Continuity integrates directly into health systems’ EMR, and also has a platform available for outpatient imaging.
Rad AI plans to use the latest round of funding to drive further development and commercialization of Rad AI Omni and Rad AI Continuity, the company’s first core offerings on its AI platform, and advance Rad AI’s mission to empower radiologists with AI — saving them time, reducing burnout, and helping to improve the quality of patient care.
“At Rad AI, we’ve always believed that AI will augment and benefit radiologists, not replace them,” said Doktor Gurson, co-founder and CEO of Rad AI. “Radiology is an extraordinarily complex field, of which image pattern recognition is only a small part. By building products that put the radiologist and patient first we’ve been able to break through the noise and focus on what really matters — reducing radiologist fatigue and improving patient care.”