Browse these articles and videos to learn more about how Flywheel provides a compliant solution to accelerate imaging research for pharma, medical device, and other life science research.
Learn how pharma researchers are accessing and efficiently leveraging diverse datasets to take advantage of the AI boom in R&D. This video covers strategies for maximizing internal and external data.
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Streamlining Reader Workflows to Enable AI-Scale Imaging Research
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Flywheel is the revolutionary research data management platform powering healthcare innovation by accelerating collaboration, enabling machine learning, and streamlining the massive task of data aggre
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Administering reader workflows for annotation has traditionally been a challenge. Join Flywheel’s experts for a look at how annotation and labeling can work at scale in life sciences organizations.
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Hear experts from Flywheel and NVIDIA discuss the latest in imaging AI, and how pharma organizations are taking advantage of state-of-the-art tech. How can AI take pharma to the next level?
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The FAIR Data principles are accelerating drug design, clinical trials, and AI efforts. But working with complex data requires unique solutions. Learn how to implement FAIR across large enterprises.
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Flywheel’s cloud-scale data management and collaboration platform is being leveraged today by large pharmaceutical companies. We have integrated our multi-modality imaging platform into the digital ec
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Medical 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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Flywheel allows secure collaboration on biomedical data while reducing data security risks. Our data procedures and systems meet the highest standards.
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Experts from pharma, medical device, and research backgrounds discuss how organizations can accelerate pharma innovation by breaking down data silos.
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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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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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Flywheel CEO Jim Olson wrote for Drug Discovery & Development on the potential of federated learning for improving pharma AI.
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Flywheel de-identifies biomedical research data as it is captured, outside of the platform, giving researchers rapid access only to the information they need.
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Multi-reader studies bring unique workflow requirements to optimize data capture. Flywheel gives researchers custom configuration options.
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There are three ways you can import imaging research data into Flywheel. Read this quick overview, and contact us for custom advice on your situation.
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