Mass General Brigham and the University of Wisconsin School of Medicine and Public Health, along with its partnering health system, UW Health, are working with Microsoft to accelerate the use of AI in medical imaging.
The collaborations will foster research tied to the advancement of high-performing multimodal AI foundation models that empower the entire radiology ecosystem to build on top of the Microsoft Azure AI platform and extend the Nuance suite of radiology applications to create an array of medical imaging copilot applications.
Grappling with staffing shortages and physician burnout, healthcare organizations are looking to generative AI to help reduce workloads, enhance workflow efficiencies, and improve the accuracy and consistency of medical image analysis for care delivery, clinical trials recruitment and drug discovery. Generative AI in radiology also may help enhance patient experiences by reducing wait times for imaging results, further opening up access to care and improving the quality of care, Microsoft notes.
Researchers and clinicians at Mass General Brigham, UW School of Medicine and Public Health, and UW Health will collaborate on the development, testing and validation of the latest breakthrough technology, deploying real-world use cases into clinical workflows, including via Nuance’s PowerScribe radiology reporting platform, used by the majority of radiologists in the U.S., and the Nuance Precision Imaging Network, which offers a single point of access to automate and scale use of third-party medical imaging AI models for a range of modalities and specialties.
“Generative AI has transformative potential to overcome traditional barriers in AI product development and to accelerate the impact of these technologies on clinical care. As healthcare leaders, we need to carefully and responsibly develop and evaluate such tools to ensure high-quality care is in no way compromised,” said Keith J. Dreyer, D.O., Ph.D., chief data science officer and chief imaging officer at Mass General Brigham and leader of the Mass General Brigham AI business, in a statement. “Foundation models fine-tuned on Mass General Brigham’s vast multimodal longitudinal data assets can enable a shorter development cycle of AI/ML-based software as a medical device and other clinical applications, for example, to automate the segmentation of organs and abnormalities in medical imaging and increase radiologists’ efficiency and consistency.”
“Our institutions have a reputation for embracing technical innovations as opportunities to lead the transformation of our field with new scientific discovery and improvement in clinical care,” said Scott Reeder, M.D., Ph.D., chair of the Department of Radiology, University of Wisconsin School of Medicine and Public Health, and radiologist at UW Health, in a statement. “We are excited to collaborate with Microsoft on the development, validation and thoughtful clinical investigation of generative AI in the medical imaging space. Our focus is to bridge the gap within medical imaging from innovation to patient care in ways that improve outcomes and make innovative care more accessible.”
