Check out our article collection for insights from Flywheel on platform updates, how our users are tackling challenges in research data management, and more.
King’s College London and the Bill and Melinda Gates Foundation UNITY Project use Flywheel as a medical image sharing hub for international research into health outcomes and child brain development.
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The growth of AI has raised expectations for good data management and data quality. Learn how to adapt to new standards of data tagging and medical imaging data integration.
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Is it counterproductive for drug developers to squander time and resources piecing together data management infrastructure for AI? Learn about data management realities that pose challenges to AI.
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Radiologists cut 8 months of processing time leveraging Flywheel and NVIDIA. See how they access millions of images, annotate data efficiently, and train and deploy medical imaging AI models.
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See how Flywheel’s platform enables AI in pharma R&D for smarter use of large volumes of imaging & delves into the unique challenges in handling and curating data for model creation.
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View NowMedical imaging holds great potential in life sciences R&D, but it can be time-consuming to leverage. The right data management and computation tools can accelerate breakthroughs and improve outcomes.
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Dr. Peter McCaffrey at UTMB is leveraging Flywheel to enable research collaborations and make AI-ready data sets. Read the details of his unique approach.
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This article from Drug Discovery & Development explains how pharma research teams can unite legacy data, including imaging data, to better characterize disease mechanisms and therapeutic responses.
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Read how 19 institutions are collaborating on Flywheel on the Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) study.
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The NIH data management and sharing mandates are now in effect. Flywheel offers a complete, enterprise-scale solution for governance and compliance with DMS policies.
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Flywheel's medical director, Aaron Mintz, spoke with Radiology Today about how federated learning holds promise to accelerate breast imaging AI research and improve patient outcomes.
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Read how Dr. Azeezat Azeez and her collaborators are using Flywheel to automate research workflows for Stanford Neuromodulation Therapy.
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Learn how Flywheel streamlined data access at an imaging core studying cancer biomarkers and multimodal imaging.
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The Yassa Lab at UC Irvine uses Flywheel as its data platform for a multicenter collaboration on biomarkers of Alzheimer's disease in Down syndrome. Its success has driven further adoption in the lab.
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Flywheel CEO Jim Olson wrote for Drug Discovery & Development on the potential of federated learning for improving pharma AI.
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Check out our article for Drug Discovery & Development calling on our experts' real-world experience with digital transformation and how pharma companies can be successful with AI.
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