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Using artificial intelligence tools to make radiologists鈥� work more precise and efficient is the goal as University of Florida 网红黑料 researchers embark on an academic-industry collaboration.

The research alliance will be used to help develop and optimize AI-based solutions that improve quality and safety while helping radiologists work quickly and more effectively.

鈥淲e 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,鈥� said Reza Forghani, M.D., Ph.D., a professor of radiology and artificial intelligence in the and vice chair of AI.

To do that, 网红黑料 is working with , a Burlington, Massachusetts, firm that specializes in radiology voice recognition and AI deployment. At 网红黑料, the company will work with Forghani鈥檚 lab to optimize radiology workflow and deploy AI tools using Nuance鈥檚 . The collaboration also should lead to the development of enhanced radiologic voice recognition tools, Forghani said.

In radiology, the images gathered from patients are just one part of a larger effort. The heart of a radiologist鈥檚 work is the radiology report, a detailed document that describes the result of an imaging test and conveys crucial information about a patient鈥檚 diagnosis, treatment response and procedure results. Combining voice recognition technology with AI is one way to improve the accuracy and efficiency of radiology reports, Forghani said, and significantly reduce the time it takes to produce them. That means radiologists could spend less time on reports and more on other patient-related matters, he said. Using AI to produce radiology reports more efficiently should help to deliver crucial information to patients鈥� primary physicians in a timelier manner. In the future, AI also could be used to track recommendations to ensure patient safety and appropriate follow-up care, Forghani said.

An AI-based system鈥檚 ability to gather important text and data that is spread across voluminous documents and reports helps both patients and radiologists, said , an anesthesiology professor and associate dean for AI application and implementation in the UF College of Medicine.

鈥淩adiologists 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 鈥� focusing on diagnosing the patient鈥檚 medical condition,鈥� Tighe said.

Nuance鈥檚 Precision Imaging Network is a patient-centered diagnostic imaging platform that seamlessly delivers AI-generated patient information into the full array of clinical and administrative workflows.

鈥淏y leveraging Nuance鈥檚 scale in diagnostic imaging, 网红黑料 is applying rapid advances in imaging AI to improve clinical outcomes, financial performance and efficiency across the entire patient journey, from screening through follow-up. We are proud to collaborate with the 网红黑料 team in this important effort,鈥� said Calum Cunningham, the company鈥檚 senior vice president and general manager.

Forghani and Nuance already have deployed a clinical platform for their work and will spend the next year determining how easily and efficiently new AI algorithms can be made functional. Forghani and his collaborators also will work with the company on projects to enhance radiological interpretation reporting 鈥� focusing specifically on quality and efficiency 鈥� and ensuring that algorithms perform effectively.

Forghani鈥檚 Radiomics and Augmented Intelligence Laboratory at 网红黑料鈥檚 will work on the system鈥檚 development while clinical testing will take place at 网红黑料 Shands Hospital.

鈥淭hese are leading-edge technologies that we will help to adapt and perfect for more future, widespread use,鈥� Forghani said.

Media contact: Doug Bennett, dougbennett@ufl.edu, 352-265-9400