Cloud-Scale COVID-19 AI Research and Collaboration in Radiology
Tuesday, June 29th at 1pm EDT
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 compliance standards and supporting secure sharing across multiple institutions. Learn how a small, investigator-initiated project developed into a valuable COVID-19 chest CT dataset with Flywheel and how Imbio is exploring the correlation between lung injury severity and patient prognosis, as well as developing AI to diagnose COVID-19. Join us to learn how to capture value from your imaging data, improve R&D efficiency, and shorten clinical trial timelines.
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 complexity by supporting research collaboration and enabling open science at the point of data access. Flywheel's Michael Perry discusses how the centralized platform streamlines BIDS in an end-to-end solution for data management and collaboration.
Dr. John Garrett, Director of Informatics at the University of Wisconsin Department of Radiology, discusses the state of machine learning in medical imaging and his development of AI to diagnose COVID-19 using thousands of chest X-rays collected and curated in Flywheel. Brad Genereaux explains how NVIDIA facilitates rapid AI training and Travis Richardson overviews Flywheel’s ecosystem for collaboration between academia, clinical organizations and life sciences.
Can Akgun, SVP of Business Development at Flywheel, discusses streamlining the ingestion of diverse data from internal and external sources and Flywheel’s ability to scale processing and support machine learning workflows.