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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See how leading researchers have applied Flywheel to accelerate their work, simplify collaborations, and streamline their research data management.
We discuss how to build reliable, scalable solutions that integrate advanced AI technology and enable robust imaging data management and analysis.
Watch Video
Flywheel is the medical imaging data platform for a multi-institutional partnership sponsored by the National Institutes of Health, the INCLUDE project, to generate insight into pediatric disease.
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King’s College London and the Bill and Melinda Gates Foundation UNITY Project use Flywheel as a medical image sharing hub for international research into health outcomes and child brain development.
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We use one platform to conduct a comparison of two deep learning liver and kidney segmentation models, revealing the importance of complete DICOM header curation to reduce segmentation errors.
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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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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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Read how Dr. Azeezat Azeez and her collaborators are using Flywheel to automate research workflows for Stanford Neuromodulation Therapy.
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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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Stanford Medicine’s Brain Stimulation Lab uses Flywheel to automate clinical research workflows & manage large volumes of psychiatric data in its clinical trials on treatment-resistant depression.
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Data management is key to the development of AI and often accounts for 80% of researchers' workload leaving minimal time for analysis. There are many challenges to getting high-quality data into the h
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Learn how Flywheel streamlined data access at an imaging core studying cancer biomarkers and multimodal imaging.
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The Yassa Lab at UC Irvine uses Flywheel as its data platform for a multicenter collaboration on biomarkers of Alzheimer's disease in Down syndrome. Its success has driven further adoption in the lab.
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If you’re curious about how Flywheel’s openness and extensibility can come to life in the hands of a power user, don’t miss this chat with Anisha Keshavan, senior data scientist at Octave Bioscience.
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Precision neuroscience has the potential to revolutionize diagnosis, treatment, and rehabilitation for the growing incidence of traumatic brain injury (TBI). To pave the way for a new era of clinical
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Read how 19 institutions are collaborating on Flywheel on the Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) study.
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The Dornsife Neuroimaging Center uses Flywheel’s research data platform to support research productivity across the University of Southern California community.
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Data management is a key component to developing AI software. Organizations need adaptable, scalable infrastructure that can provide access to curated data while maintaining strict privacy and complia
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In this conversation with Dr. Timothy Verstynen, Co-Director at the Carnegie Mellon University - University of Pittsburgh BRIDGE Center, hear how the Center addresses the problem of increasing data co
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Check out Google Cloud's case study for a look at how the Stanford CNI and the Stanford VISTA Lab are using Flywheel to manage, share, and analyze scientific data.
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