Accelerated Drug Development through Scalable AI-Powered Medical Imaging
We discuss how to build reliable, scalable solutions that integrate advanced AI technology and enable robust imaging data management and analysis.
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Ready to learn more about how Flywheel streamlines data management for imaging researchers? Browse our articles, case studies, and videos to see how leading researchers are applying our tools.
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Advancing Imaging AI Development With NVIDIA and Flywheel
Radiologists cut 8 months of processing time leveraging Flywheel and NVIDIA. See how they access millions of images, annotate data efficiently, and train and deploy medical imaging AI models.
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AI in Medical Imaging: Streamlining Reader Workflows for Expedited Model Development
Watch this webinar to gain insights from real-world pharma use cases to unlock the potential of AI. We demystify the process of labeling and annotating medical images. Learn how to efficiently guide e
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What is Flywheel?
Flywheel is the pioneering medical imaging AI development platform powering healthcare innovation through streamlined data management, curation and analysis. Flywheel helps organizations turn complex
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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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Tackling the Challenges of Imaging-Based AI in Pharma R&D
See how Flywheel’s platform enables AI in pharma R&D for smarter use of large volumes of imaging & delves into the unique challenges in handling and curating data for model creation.
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Flywheel for Reader Studies: Demo
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 Enterprise Demo
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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Diverse Datasets — How to Find, Curate & Leverage them to Fuel AI 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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Harnessing the untapped potential of legacy data in pharma R&D
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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Streamlining Reader Studies & Medical Imaging Workflows in R&D
Flywheel’s experts look at the state of medical imaging workflows and reader studies and discuss how annotation and labeling can work at scale in life science R&D. Click to watch the full webinar.
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[Listen] Enterprise-Scale Imaging Data Science: Future-Ready Strategies
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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Designing Custom Multi-Reader Studies is Streamlined with Robust Viewer Configuration Options
Multi-reader studies bring unique workflow requirements to optimize data capture. Flywheel gives researchers custom configuration options.
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Leveraging Imaging AI for Pharma Breakthroughs: What’s Next?
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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Federated learning project connects pharma with university to train AI model
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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Leveraging Next-Generation Tools for Enterprise-Level Dataset Creation
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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Federated Learning: A Different Type of House Call
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 and Reuse for Healthcare Innovation: Preparing for the NIH Mandate and Beyond
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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Smart Copy helps Flywheel sites share and manage data more efficiently
Flywheel’s Smart Copy feature gives users options for sharing and reusing data and analysis while minimizing storage use.
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FAIRifying Medical Imaging Data: Accelerating Large-Scale Data Initiatives
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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