Resources
Flywheel for Healthcare Research
White Paper: Hybrid Infrastructure to Accelerate AI Model Training & Development
In today’s competitive landscape, medical device companies are evolving toward software-defined systems where success in next-generation healthcare depends on parallel, integrated AI and data…
Advancing Imaging AI Development With NVIDIA and Flywheel
Imaging AI development demands navigating complex, regulated, and scattered data, often consuming up to 80% of data scientists' time. UW-Madison researchers harnessed the power…
Algorithm Bake-Off: Comparing AI Algorithms for CT Segmentation with Flywheel Data Exchange and Jupyter Notebooks
In this white paper, see an example of using an imaging data management platform to conduct a comprehensive comparison of two deep learning-based CT…
Executive Brief: The Business Case for Investing in a Medical Imaging AI Platform
What if you could double the number of projects this year without adding to your IT department’s workload—all in service of accelerating AI development,…
Why You Need a Validated Imaging Data Management Solution
Learn if your imaging research needs to meet 21 CFR Part 11 and how to maintain compliance.
White Paper: How Imaging Can Drive More Effective Combination Immunotherapy in Oncology
Immunotherapy offers hope for patients with various malignancies. But the complexity of tumor microenvironments and the variability in patient responses necessitate more personalized approaches…
White Paper: Unlocking Value in Your Medical Imaging Data for Accelerated AI Development
Medical imaging data has the power to improve diagnostic accuracy, unlock new treatments and advance patient care. But medical enterprises face unique hurdles in…
White Paper: Medical Imaging Platforms: Ending the Build vs. Buy Debate
Medical imaging and video data fuel pharma and medtech innovation—but a lack of standardization, restricted access and fragmented sources across the globe often keep…
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