University of Florida Health Announces AI-Driven Radiology Initiative
New research collab between University of Florida Health and Nuance will focus on the development and integration of AI-based radiology tools.
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By - University of Florida (UF) Health and Nuance Communications Inc., a Microsoft company, have launched a collaboration aimed at leveraging artificial intelligence (AI) to make radiologists’ work more efficient and precise.
Under the collaboration, UF Health will tap Nuance’s expertise in radiology voice recognition and AI deployment.
“We intend to accelerate development of solutions that enable seamless integration of AI into clinical practice. Those improvements will provide higher quality, cost-effective processes for improving patient care,” said Reza Forghani, MD, PhD, a professor of radiology and artificial intelligence in the UF College of Medicine and vice chair of AI, in the press release.
Forghani’s lab will work with Nuance to optimize radiology workflows and deploy AI tools within UF Health using the company’s Precision Imaging Network. The two organizations also expect to develop enhanced radiologic voice recognition tools as part of the collaboration.
Much of this work will focus on improving the accuracy and efficiency of radiology reports while reducing the time it takes to produce them, the press release notes.
Radiology reports describe the results from imaging tests and help convey key information about a patient’s diagnosis, treatment response, and procedure results. This information is often spread across multiple other documents and reports, making radiology reports particularly time-consuming to generate.
AI and voice recognition may help improve this process, allowing clinicians to spend more time on patient care.
“Radiologists are under more and more pressure to interpret progressively complex medical images with increasingly sick patients. By streamlining the reporting, a system like this helps them focus on the most rarified and special parts of what they do — focusing on diagnosing the patient’s medical condition,” explained Patrick Tighe, MD, an anesthesiology professor and associate dean for AI application and implementation in the UF College of Medicine, in the press release.
By using AI to produce radiology reports, critical information can be delivered to primary care physicians in a timelier manner, Tighe indicated.
Forghani noted that in the future, such tools may be able to track recommendations for follow-up care and patient safety.
Currently, Forghani and Nuance are evaluating an already-deployed clinical platform to support these efforts. Over the next year, UF Health and Nuance will assess how efficiently new AI tools can be made functional.
Forghani’s lab will also work with Nuance on projects to enhance radiological interpretation reporting, with a focus on quality and efficiency. The Radiomics and Augmented Intelligence Laboratory at UF Health’s Norman Fixel Institute for Neurological Diseases will spearhead development while clinical testing will take place at UF Health Shands Hospital.
This initiative reflects a broader interest in using AI to improve radiology care.
In October, researchers from the University of Iowa shared that they are developing an artificial intelligence-based device to help address healthcare staffing challenges and mitigate care team risk by performing simple interventional radiology tasks and procedures.
