Microsoft Collaborates with Mass General Brigham & University of Wisconsin-Madison on AI in Medical Imaging

The collaboration aims to develop, test, and validate AI algorithms and applications to improve the accuracy and consistency of medical image analysis. 

Microsoft is expanding its healthcare AI initiatives by partnering with Mass General Brigham and the University of Wisconsin-Madison to advance artificial intelligence in medical imaging. 

The collaboration aims to develop, test, and validate AI algorithms and applications to improve the accuracy and consistency of medical image analysis. 

This effort is expected to help healthcare organizations create AI copilots for medical imaging, enhance radiologists' and clinicians' capabilities in interpreting medical images, and assist with report generation, disease classification, and structured data analysis.

Integrating AI into Clinical Workflows

Per the collaboration, researchers and clinicians from Mass General Brigham, UW School of Medicine and Public Health, and UW Health will work with Microsoft to advance multimodal foundation models. 

These AI models will be built on the Microsoft Azure AI platform and integrated into clinical workflows via Nuance’s PowerScribe radiology reporting platform, widely used by US radiologists, and Nuance’s Precision Imaging Network.

Highlighting the potential impact of the collaboration, Keith J Dreyer, DO, PhD, chief data science officer and chief imaging officer at Mass General Brigham, said, "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.”

He further noted that 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.

Addressing Industry Challenges

The healthcare industry faces significant challenges, including rising rates of physician burnout and staffing shortages. Health systems spend approximately $ 65 billion annually on imaging, and about 80% of hospital and health system visits involve at least one imaging exam. 

Additionally, many hospitals and health systems are exploring generative AI tools to reduce workloads, enhance workflow efficiencies, and improve the accuracy and consistency of medical image analysis for various applications, including care delivery, clinical trial recruitment, and drug discovery.

Scott Reeder, MD, PhD, chair of the Department of Radiology at the University of Wisconsin School of Medicine and Public Health and radiologist at UW Health, said,

"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.”

This collaboration is part of Microsoft's broader effort to advance the use of generative AI in healthcare. Microsoft is also working with chipmaker Nvidia to enhance generative AI, the cloud, and accelerated computing for healthcare and life sciences organizations. 

In March, Microsoft and Nvidia announced a partnership to combine Microsoft Azure's advanced computing capabilities with Nvidia DGX Cloud and the Nvidia Clara suite of computing platforms, software, and services.