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Rad AI Raises $4M to Automate Repetitive Tasks for Radiologists Through Machine Learning

by Fred Pennic 11/25/2019 Leave a Comment

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Rad AI Raises $4M to Automate Repetitive Tasks for Radiologists Through Machine Learning

– Rad AI raises $4M in seed funding led by Gradient Ventures, Google’s AI-focused venture fund to transform radiology with the latest advances in AI to save radiologists 60+ minutes a day.

– By streamlining existing workflow and automating repetitive manual tasks, Rad AI increases daily productivity while reducing radiologist burnout. 

– Rad AI provides more consistent radiology reports for ordering clinicians, and higher accuracy for the patients it serves.

Berkeley-based Rad AI, a digital health startup using machine learning to transform the practice of radiology, today announced its company launch and a $4 million seed round led by Gradient Ventures, Google’s AI-focused venture fund. Investors UP2398, Precursor Ventures, GMO Venture Partners, Array Ventures, Hike Ventures, Fifty Years VC and various angels also participated in this round.

Today, radiology groups face increased competition and unrelenting market consolidation. While keeping up with the growing demand and complexity of their workflows, radiologists continue to struggle with meeting RVU goals. In addition, there is a drastic and growing shortage of radiologists. According to WHO, two-thirds of the world does not have access to radiology services. In areas that do, radiologist burnout, error rates, and turnaround times continue rising. The result: overloaded radiologists, crumbling medical workflows, and inadequate patient care.

Designed by Radiologists, for Radiologists

Rad AI Raises $4M to Automate Repetitive Tasks for Radiologists Through Machine Learning
Co-Founders Doktor Gurson (Left) and Dr. Jeff Change (Right)

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.

“Radiology is facing severe pressures that range from falling reimbursements to market consolidation. There is also a radiologist shortage that is exacerbated by rising imaging volumes nationwide.  We help radiology groups significantly increase productivity, while reducing radiologist burnout and improving report accuracy. By working closely with radiologists, we can make a positive impact on patient care,” said Dr. Chang.

AI-Driven Solution Saves Radiologists 60+ Minutes A Day

Automated Report Impressions

Comprised of both radiology and AI expertise, Rad AI’s stellar team builds products that maximize radiologist productivity, ultimately making healthcare more widely accessible and improving patient outcomes. By streamlining existing workflow and automating repetitive manual tasks, Rad AI increases daily productivity while reducing radiologist burnout. Rad AI saves radiologists an average of more than 60 minutes per day.

Using the latest state-of-the-art artificial intelligence, their solution automatically generates report impressions, customized to their exact language. This means 35% fewer words dictated, more consistent reports and recommendations, and decreased radiologist burnout.

Traction/Milestones

Rad AI’s current partners include Greensboro Radiology, Medford Radiology, Einstein Healthcare Network, and BICRAD, the 8th largest private radiology group in the United States, as well as other radiology groups that have yet to be announced. Product rollouts have demonstrated an average of 20% time savings on the interpretation of CTs and 15% time savings on radiographs — translating into an hour a day saved for each radiologist. Rad AI plans to use the latest capital to build out its engineering team and expand the rollout of its first product to more radiology groups and customers.

RELATED:   Eko Unveils Redesigned Smart Stethoscope and Stethoscope Attachment

Tagged With: Artificial Intelligence, Machine Learning, Physician Burnout, Rad AI, Radiologist

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