Flywheel Unveils New Viewer Updates at RSNA
Flywheel has made updates to its built-in viewer that address more of researchers’ key challenges when analyzing imaging data.
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Check out these details about our product features to understand more about how Flywheel can streamline your work and collaborations.
Flywheel has made updates to its built-in viewer that address more of researchers’ key challenges when analyzing imaging data.
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View NowDive deeper: register for a hands-on learning lab at RSNA!
Learn MoreIn this white paper, we explore how organizations can follow 21 CFR Part 11 in clinical trials involving imaging data for submitting novel drug-based therapies and creating approvable, usable AI.
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Chapters: 0:00 Introduction 0:10 Data Exchange 0:34 Data Import 0:51 Gears & Gear Rules 1:11 Reader Studies 1:55 ML Workspaces 2:06 Model Training 3:04 Outro
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Flywheel's medical imaging data and AI platform accelerates research by helping you curate analysis-ready data. In this video, we demonstrate testing a trained classification model on mammograms to ca
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See an example of an Alzheimer’s study on the Flywheel medical imaging AI development platform, that involves discovering brain MRI images and filtering them to create the cohort we need. With that d
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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 has received a grant from the Gates Foundation to support research on neurodevelopment in low- and middle-income countries (LMICs).
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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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Flywheel’s Smart Copy feature gives users options for sharing and reusing data and analysis while minimizing storage use.
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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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Multi-reader studies bring unique workflow requirements to optimize data capture. Flywheel gives researchers custom configuration options.
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Flywheel accelerates ophthalmological imaging research through a suite of optical coherence tomography (OCT) annotation tools and customization options.
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3D Slicer users can leverage Flywheel for cloud-based data curation and management, then use their favorite 3D Slicer algorithms.
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Enhance your data visualization with an Autochart Tool from Flywheel for an efficient research workflow. Learn more about our Autochart Tool.
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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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Simplify secure data collection from research partners and contract research organizations, curate to common standards, run analyses at scale, and more.
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Flywheel integrates data from EDC systems, including REDCap. Search clinical metadata in one place, greatly streamlining your data curation.
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DICOMs in Flywheel projects may be accessed with any standard DICOM viewers and tools, enabling collaboration with radiologists and integration with existing workflows.
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Flywheel's API supports diverse data types and custom workflows through the Flywheel user interface (UI).
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Flywheel’s support for federated identity management lets users connect to collaborators at different institutions and streamline deployment.
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