STAR Teleradiology Expands Agreement with Rad AI for Omni

Tampa, FL (August 2, 2022) -- STAR Teleradiology, a Florida-based radiology practice with over 75 years of experience, announced it is expanding its partnership with Rad AI, the nation’s fastest-growing radiologist-led AI company, to use its advanced technology in generating customized radiology report impressions to their entire practice. This expansion builds on STAR Teleradiology’s commitment to deliver expert, accurate, and timely diagnostic imaging interpretation services. 

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“I knew from the first time I used Rad AI Omni it would be a complete game-changer by allowing us to turn around the highest-quality reports faster with fewer addenda,” said Dr. Darren Buono, CEO & Co-Founder of STAR Teleradiology. “Of all the technology and solutions that we’ve implemented for our practice, Rad AI Omni has made the biggest impact on our efficiency and quality. I have personally reached out to colleagues of mine to prioritize a partnership with Rad AI.”

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Rad AI’s Omni solution automatically generates a customized radiology report impression from the findings and clinical indication dictated by the radiologist, using state-of-the-art neural networks. It learns each radiologist’s language preferences from their prior reports to create an impression that the radiologist can simply review and finalize. 

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In addition, Rad AI improves report accuracy and consistency by automatically including significant incidental findings, helping to answer the main clinical question, and providing the latest 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.

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“We are excited to know that Rad AI Omni has been so valuable to an organization like STAR Teleradiology that relies on quick and accurate readings to help offset their busy emergency room shifts and high volumes,” said Dr. Jeff Chang, ER radiologist and co-founder of Rad AI. “To know that we’ve exceeded their expectations and they decided to expand their agreement to their entire practice solidifies the value that our product is bringing to market.”

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About STAR Teleradiology: 

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STAR Teleradiology was formed by a core group of radiology with over 75 years of experience. The practice is dedicated to providing expert, accurate interpretations of diagnostic imaging studies by board-certified and fellowship-trained radiologists. STAR Teleradiology’s radiologists have expertise in MRI, CT, US, and X-ray with specific diagnostic expertise in Orthopedic and Sports imaging, as well as neuroradiology, spine imaging, urological, and trauma imaging. 

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STAR Teleradiology is committed to providing exceptional service to our imaging partners by delivering expert, accurate, and timely diagnostic imaging interpretation services. We work personally with each and every client to understand their individual imaging needs while minimizing costs, optimizing efficiency, and improving patient care. 

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Learn more about STAR Teleradiology at https://startelerad.com/. 

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About Rad AI:

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Rad AI is the fastest growing radiologist-led AI company. In addition to winning the 2021 award for “Best New Radiology Vendor” from AuntMinnie, Rad AI ended the year by being named to the 2021 CB Insights Digital Health 150 list of “Most Innovative Digital Health Startups.” In 2022, Black Book ranked Rad AI #1 in Mean KPI score on its survey revealing 50 emerging solutions challenging the healthcare technology status, and Rad AI continued the momentum by being recognized in the 2022 CB Insights list of “100 Most Promising AI Companies.”

Founded in 2018 by the youngest radiologist in US history, Rad AI has seen rapid adoption of its AI platform, and is already in use at 8 of the 10 largest private radiology practices in the US. 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.

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Learn more about Rad AI at www.radai.com or on Twitter @radai.

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