Rad AI partners with Google for cloud-based reporting innovation
Rad AI announced its new partnership with Google this week, where the radiology startup will leverage the cloud giant’s artificial intelligence capabilities to further streamline reporting and reduce administrative burden.
WHY IT MATTERS
Under the partnership, Rad AI will leverage the Google Cloud platform and tools such as MedLM, a family of base models tailored to healthcare use cases, including Gemini-based models in the future.
Google Cloud, meanwhile, will become Rad AI’s cloud provider of choice, helping the startup build out and improve its platforms, Rad AI Omni Impressions and Rad AI Reporting, with domain-centric generative AI models.
That will help Rad AI automatically generate a larger portion of the radiology report, customized to each radiologist’s preferred language and style – saving time while improving the quality and consistency of reports.
Rad AI will also be able to scale the size and complexity of its Rad AI Omni Impressions and Rad AI Reporting gen AI models, the company says, enabling greater clinical accuracy, personalization and performance gains.
“This partnership represents an exciting step forward in our commitment to transform the radiology reporting landscape,” said Doktor Gurson, co-founder and CEO of Rad AI, in a statement. “Through this unique partnership with Google, we can dramatically accelerate our mission to reduce radiologist burnout, streamline workflow and ultimately improve the quality of patient care.”
THE BIG TREND
Imaging data accounts for approximately 90% of all healthcare data, and the number of imaging studies performed each year is only increasing – adding to the already heavy workload for radiologists, who spend hours dictating reports based on these images . Rad AI says its tools can reduce the number of words needed for dictation by as much as 90%.
Artificial intelligence is transforming all aspects of the radiology reading and reporting process and reshaping the workflows of imaging professionals, like Dr. Benoit Desjardins, professor of radiology at Penn Medicine, recently explained.
Meanwhile, new FDA approvals, proprietary advances in imaging developed at academic medical centers, and new tools from other vendors are fueling the AI-enabled transformation of radiology practices.
Yet there are challenges we must guard against, related to bias, safety and more.
ON THE RECORD
“Radiology is a field that will see immediate, high-value impact from advances in generative AI, and radiology reporting is an area where this technology can have a meaningful impact,” said Aashima Gupta, Global Director of Healthcare Strategy and Solutions at Google . Cloud. “As the number of medical images continues to grow, our goal is to enable the ecosystem and help our customers equip radiologists with the latest generative AI capabilities not only to manage workflows but also to improve patient treatment through faster and more accurate diagnoses.”
Mike Miliard is editor-in-chief of Healthcare IT News
Email the writer: mike.miliard@himssmedia.com
Healthcare IT News is a HIMSS publication.