Using artificial intelligence tools to make radiologists’ work more precise and efficient is the goal as University of Florida Health 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.
“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, M.D., Ph.D., a professor of radiology and artificial intelligence in the UF College of Medicine and vice chair of AI.
To do that, UF Health is working with Nuance Communications Inc., a Burlington, Massachusetts, firm that specializes in radiology voice recognition and AI deployment. At UF Health, the company will work with Forghani’s lab to optimize radiology workflow and deploy AI tools using Nuance’s Precision Imaging Network. 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’s work is the radiology report, a detailed document that describes the result of an imaging test and conveys crucial information about a patient’s 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’ 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’s ability to gather important text and data that is spread across voluminous documents and reports helps both patients and radiologists, said Patrick Tighe, M.D., an anesthesiology professor and associate dean for AI application and implementation in the UF College of Medicine.
“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,” Tighe said.
Nuance’s 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.
“By leveraging Nuance’s scale in diagnostic imaging, UF Health 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 UF Health team in this important effort,” said Calum Cunningham, the company’s 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 — focusing specifically on quality and efficiency — and ensuring that algorithms perform effectively.
Forghani’s Radiomics and Augmented Intelligence Laboratory at UF Health’s Norman Fixel Institute for Neurological Diseases will work on the system’s development while clinical testing will take place at UF Health Shands Hospital.
“These are leading-edge technologies that we will help to adapt and perfect for more future, widespread use,” Forghani said.
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