Flywheel allows you to develop, test and verify imaging models in your preferred environments, and ensure that all versions and results can be found alongside your source data. Pull analysis-ready data sets for training and testing into the AI development tools you already know and use.
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UW-Madison researchers harnessed the power of Flywheel and NVIDIA Healthcare to enhance patient outcomes and reduce manual data processing work from eight months, down to one day.
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Develop machine learning in medical imaging at scale with curated data in an end-to-end platform. Share Azure ML Studio models with collaborators in Flywheel to test across projects and prevent redundant model-building.
Experience an end-to-end imaging data management platform with NVIDIA’s model training capabilities at scale. Access a container pre-loaded with MONAI algorithms, ready for you to explore in your environment. Choose from domain-specific algorithms, test & verify them on your data, and make adjustments as needed.
Empower developers to explore data, assign machine learning cohorts, and begin experimenting. Write executable code that can access project data, track notebook versions, and organize model results. Distill critical outputs from developed algorithms in a simple UI, and share them with stakeholders.
Publish Gears, the Flywheel plug-in applications that automate routine tasks, including metadata extraction, classification, quality assurance, format conversion, and full analytic pipelines.
