Diverse Datasets — How to Find, Curate & Leverage them to Fuel AI Research

Life Sciences, Clinical Trials,
  • Thursday, January 19, 2023

R&D departments are gravitating toward cloud-scalable, data-driven strategies to take advantage of the artificial intelligence (AI) boom. But AI is incredibly data-hungry, and many life sciences organizations are looking for better ways to feed the beast, by accessing and leveraging both internal and external datasets.

To make internal data most useful, enterprises need to establish basic data management practices for centralization, curation and computing. This has been especially challenging for imaging data, given its complex nature. MR and CT scans, X-rays and other imaging data hold tremendously valuable information for AI but extracting and cataloging this data can seem prohibitive at an enterprise level.

Similar problems apply when seeking external data — with additional challenges in costs, compliance and ensuring quality and consistency. Some researchers are beginning to leverage federated learning & analytics — sending algorithms to data where it resides — to sidestep challenges with compliance and data privacy. This approach holds great promise, but the basic data management issues remain, and researchers need mechanisms to understand the quality, scope and other attributes of a dataset before using it in a federated learning effort.

Join Flywheel’s experts in imaging research and data governance for a discussion of how these issues are playing out in life sciences organizations. How can research teams better take advantage of datasets both inside and outside their walls to train AI models and accelerate R&D? And how are organizations planning for the future while also dealing with research challenges in the here and now?


Can Akgun, Flywheel

Can Akgun, PhD, Senior Vice President of Business Development, Flywheel

Can (“John”) Akgun, PhD, is the SVP of Business Development of Flywheel. He brings over 15 years of experience in medical imaging spanning academic research, product development and commercialization. Can holds a BS and MS in electrical engineering and a PhD in biomedical engineering from the University of Minnesota.

Message Presenter
Costas Tsougarakis, Flywheel

Costas Tsougarakis, Vice President, Life Sciences Solutions, Flywheel

Costas Tsougarakis is Flywheel’s Vice President of Life Sciences Solutions. Costas has over 20 years of experience in research, development and delivery of scientific information systems in the medical device, clinical research and pharmaceutical domains with an emphasis on biomedical imaging. He joined Flywheel from Genentech, where he led the development of the Roche Global Imaging Platform, based on FAIR principles, which enables at-scale image data storage, ingestion, curation and analysis.

Message Presenter

Who Should Attend?

  • Data Scientists
  • Digital Transformation
  • Analytics/Data Management
  • AI & ML researchers
  • Imaging & Translational Imaging Researchers
  • Heads of Digital Markets and Tech
  • Digital Medicine
  • Data Partnerships
  • Technology Partnerships

What You Will Learn

Attendees will learn about:

  • The issue of “data deserts” in artificial intelligence (AI) research
  • Tools for standardizing how data is captured, curated and shared
  • How standardizing curation can speed AI development
  • Examples of life sciences successes in leveraging federated learning and diverse data

Xtalks Partner


Flywheel is the revolutionary research data management platform powering healthcare innovation by accelerating collaboration, enabling machine learning, and streamlining the massive task of data aggregation, curation and management. By leveraging cloud scalability and automating research workflows, Flywheel helps organizations scale research data and analysis, improve scientific collaboration and accelerate discoveries. Flywheel offers comprehensive solutions for life sciences, pharmaceutical, biotech, academic, and clinical research. Flywheel is headquartered in Minneapolis and has offices in the Bay Area, St. Louis, and Budapest.

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