Microsoft continues to deepen its work in healthcare AI. The tech giant is now collaborating with academic medical systems Mass General Brigham and the University of Wisconsin-Madison to advance AI in medical imaging.
The aim is to develop, test and validate AI algorithms and applications that improve the accuracy and consistency of medical image analysis and enable healthcare organizations to build medical imaging AI copilots, the organizations said.
Researchers and clinicians at Mass General Brigham, UW School of Medicine and Public Health, and UW Health will work with the tech company to advance state-of-the-art multimodal foundation models. Microsoft and the partner health systems will research how these algorithms and applications can help radiologists and clinicians interpret medical images and assist with report generation, disease classification and structured data analysis, according to the organizations.
The AI models will be built on top of the Microsoft Azure AI platform and integrated into clinical workflows via Nuance’s PowerScribe radiology reporting platform, which is used by a majority of U.S. radiologists, and Nuance’s Precision Imaging Network.
The collaboration includes UW School of Medicine and Public Health along with its partnering health system, UW Health.
Medical imaging plays a critical role in healthcare and medical diagnoses. Health systems spend an estimated $65 billion each year on imaging, according to a JAMA study. Approximately 80% of all hospital and health system visits include at least one imaging exam related to more than 23,000 conditions, Definitive Healthcare data shows.
The healthcare industry is grappling with rising rates of physician burnout and staffing shortages. Many hospitals and health systems are exploring generative AI tools 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 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," Dreyer 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, said the collaboration with Microsoft will advance "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," Reeder said.
Microsoft also is working with chipmaker Nvidia to advance the use of generative AI, the cloud and accelerated computing to healthcare and life sciences organizations. The two companies announced a collaboration in March to bring together the advanced computing capabilities of Microsoft Azure with Nvidia DGX Cloud and the Nvidia Clara suite of computing platforms, software and services, the companies said.