Using artificial intelligence tools to make the work of radiologists more precise and efficient is the goal of University of Florida Health researchers to initiate 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 faster and more effectively.
“We want to accelerate the development of solutions that enable the seamless integration of AI into clinical practice. These improvements will provide high-quality, cost-effective processes to improve patient care,” said Reza Forgani, MD, PhD, professor of radiology and artificial intelligence in the UF College of Medicine and vice chair of AI.
To do this, UF Health Nuance Communications Inc. Working with it, a Burlington, Massachusetts, firm that specializes in radiology voice recognition and AI deployments. At UF Health, the company will work with Forghani’s lab to optimize radiology workflows and deploy AI tools using Nuance’s precision imaging network. Forgani said the collaboration should lead to the development of advanced radiologic voice recognition tools.
In radiology, images collected from patients are only one part of a larger effort. Central to the radiologist’s job is the radiology report, a detailed document that describes the results of an imaging test and reveals important information about the 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, and significantly reduce the time it takes to generate them, Forgani said. That means radiologists can spend less time on reports and more time on other patient-related matters, he said. Using AI to generate radiology reports more efficiently will help deliver critical information to patients’ primary care physicians in a timely manner. In the future, AI could be used to track recommendations to ensure patient safety and proper follow-up care, Forgani said.
An AI-based system’s ability to collect important text and data spread across large volumes of documents and reports helps both patients and radiologists, said Patrick Tighe, MD, an anesthesiology professor and associate dean of AI applications and implementation at the UF College of Medicine.
“Radiologists are under greater pressure to interpret increasingly complex medical images with increasingly sick patients. By streamlining reporting, such a system helps them focus on the most rare and specialized part of what they do – focusing on diagnosing a patient’s medical condition,” Tighe said.
Nuance’s Precision Imaging Network is a patient-centric diagnostic imaging platform that seamlessly delivers AI-generated patient information to a full array of clinical and administrative workflows.
“Using Nuance’s scale in diagnostic imaging, UF Health is applying rapid advances in imaging AI to improve clinical outcomes, financial performance and efficiency from screening through follow-up throughout the patient journey. We are proud to collaborate with the UF Health team on this important endeavor,” said Calum Cunningham, the company’s senior vice president and general manager.
Forghani and Nuance have already established a clinical platform for their work and will spend the next year determining how easily and efficiently the new AI algorithms can be implemented. Forgani and his colleagues will also work with the company on projects to improve radiological interpretation reporting – particularly focusing on quality and efficiency – and ensure algorithms work effectively.
Forgani will work on developing the radiomics and augmented intelligence laboratory system at UF Health’s Norman Fixel Institute for Neurological Diseases while conducting clinical trials at UF Health’s Shands Hospital.
“These are cutting-edge technologies that we will help adapt and perfect for future, widespread use,” said Forgani.
Media Contact: Doug Bennett, [email protected], 352-265-9400