Stanford Radiology AI Development and Evaluation Lab Announces Strategic Partnership with Radiology Partners to Advance AI Safety and Reliability in Medical Imaging
Stanford Radiology’s AI Development and Evaluation (AIDE) Lab is launching a strategic research partnership with Radiology Partners (RP), a leading technology-enabled radiology practice in the U.S, and its technology and AI division, Mosaic Clinical Technologies, to foster the development of artificial intelligence (AI) assessment and continuous monitoring methods and promote the public dissemination of their research. This partnership will leverage RP’s extensive experience in implementing AI tools across their national network of radiology practices and draw on the AIDE Lab’s expertise in AI assessment and development to create innovative solutions that strengthen the performance, trustworthiness, and accessibility of AI in imaging-based healthcare.
“This partnership allows us to learn from and help disseminate RP’s existing work in implementing and facilitating AI adoption across their practice,” said David B. Larson, MD, MBA, Founding Director of the AIDE Lab and Professor of Radiology at the Stanford Medicine Department of Radiology. “We are excited to bring the AIDE Lab’s academic capabilities to RP’s practical experience and know-how to uncover patterns in AI performance across different settings, predict AI pitfalls and biases, and further develop evaluation and monitoring frameworks that can be used throughout radiology.”
“We are thrilled to collaborate with AIDE Lab on this important and timely work,” said Nina Kottler, MD, Chief Clinical Artificial Intelligence Officer at Mosaic Clinical Technologies. “This partnership underscores our shared commitment to advancing the responsible development and integration of AI in clinical practice. By working alongside leading academic medical centers like Stanford Medicine, we can accelerate the evaluation and adoption of impactful AI solutions across our national practice and contribute to the broader scientific understanding of how AI can elevate care quality, efficiency and outcomes for patients across the world.”
This partnership will generate new insights and establish AI evaluation approaches and tools that can be applied both within Stanford Medicine entities and RP practices, and more broadly, to other institutions. Building on joint research efforts already underway, the partnership will translate RP’s real-world learnings from AI deployments into reproducible, peer-reviewed insights. The research will be conducted at Stanford University School of Medicine, Department of Radiology, and will benefit the broader global clinical community by establishing new standards and methods for AI evaluation in radiology.
This partnership between the AIDE Lab and RP represents a significant step forward. “By uniting the AIDE Lab’s research experience with RP’s clinical expertise,” remarked Akshay Chaudhari, PhD, Co-Director of the AIDE Lab and Assistant Professor of Radiology and Biomedical Data Science at Stanford University, “this partnership is poised to generate new AI evaluation and monitoring tools enabling the clinical deployment of cutting-edge AI tools while ensuring that they perform as expected and remain effective and equitable for all patients.”
David Larson, Founding Director of the AIDE Lab, in conversation with Nina Kottler from Mosaic Clinical Technologies. Image courtesy of RadPartners.
About the AIDE Lab
The Stanford Radiology AIDE Lab is dedicated to systematically improving the safety, reliability, and equity of artificial intelligence in imaging-based healthcare. With a specific focus on quality, the AIDE Lab aims to advance public trust and transparency in AI models by driving robustness and standardization in evaluation, and equipping institutions with tools for continuous AI surveillance and maintenance.
Comprised of a team with over 50 years of combined clinical, research, and industry experience in diagnostic imaging and machine learning, the Stanford Radiology AIDE Lab aims to address the challenges and complexities that exist at the intersection of AI and medicine. The team is committed to fostering collaborations with interdisciplinary groups functioning across academia, health systems, government, and industry to bridge the gap between AI innovation, and ultimately, clinical application.
For more information, visit aide.stanford.edu and connect with us on LinkedIn.