Advancing R&D by Incorporating Medical Imaging at Scale
Medical imaging holds a wealth of valuable data that can power pharma R&D. See how pharma leaders are harnessing this data with scalable tools, and the fundamentals for success.
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Insights on Research Data Management
Medical imaging holds a wealth of valuable data that can power pharma R&D. See how pharma leaders are harnessing this data with scalable tools, and the fundamentals for success.
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Take a look at Flywheel's robust and fully customizable framework for designing and orchestrating reader studies. Our video shows an oncology reader study example.
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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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View NowLearn 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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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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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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Listen to our 2022 RSNA panel discussion among experts in data science, governance, hardware, and software to learn how organizations are building smart data frameworks to power research.
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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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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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Read how Flywheel facilitated a federated learning project between a pharma company and a university with an AI model trained on x-ray data.
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The University of Texas Medical Branch has implemented a platform for streamlining the creation of radiology and pathology datasets, enabling more efficient collaborations.
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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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Data sharing is now an urgent matter for NIH-funded researchers, with new mandates going into effect in January 2023. Learn about tools for complying, plus optimizing data for sharing and reuse.
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Flywheel’s Smart Copy feature gives users options for sharing and reusing data and analysis while minimizing storage use.
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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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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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Experts from pharma, medical device, and research backgrounds discuss how organizations can accelerate pharma innovation by breaking down data silos.
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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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