Summary: Microsoft is collaborating with Mass General Brigham and the University of Wisconsin to develop AI models for radiology, aiming to improve clinician efficiency, health outcomes, and medical image analysis accuracy.
Key Takeaways:
- Microsoft is collaborating with Mass General Brigham and the University of Wisconsin to develop AI models for radiology, aiming to improve clinician efficiency, health outcomes, and medical image analysis accuracy.
- These partnerships will leverage the Microsoft Azure AI platform and Nuance’s radiology applications to innovate AI algorithms for image interpretation, report generation, disease classification, and data analysis.
- The collaborations emphasize the responsible development and evaluation of generative AI to enhance clinical care without compromising quality, supported by extensive data assets from Mass General Brigham and the University of Wisconsin.
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Microsoft Corp. announced collaborations with Mass General Brigham and the University of Wisconsin (UW) School of Medicine and Public Health, along with UW Health, to tackle challenges in radiology and advance AI in medical imaging. These partnerships aim to develop artificial intelligence (AI) models on the Microsoft Azure AI platform and extend Nuance’s suite of radiology applications. The goal is to enhance clinician efficiency and health outcomes, reduce physician burnout, and improve medical image analysis accuracy.
AI-Powered Radiology
Medical imaging is crucial, with health systems spending $65 billion annually. AI can streamline workflows and improve care quality. Microsoft’s partnerships will foster innovation in AI algorithms to assist radiologists and clinicians with image interpretation, report generation, disease classification, and structured data analysis.
“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,” says Keith J. Dreyer, DO, PhD, chief data science officer and chief imaging officer at Mass General Brigham and leader of the Mass General Brigham AI business.
Dreyer adds, “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.”
Generative AI Development
Scott Reeder, MD, PhD, chair of the department of radiology, University of Wisconsin School of Medicine and Public Health, and radiologist at UW Health, also spoke out about the partnership, commenting: “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.”
“We are excited to collaborate with Microsoft on the development, validation, and thoughtful clinical investigation of generative AI in the medical imaging space,” Reeder says. “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.”
