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ACR 2017 The Crossroads of Radiology


ACR2017VM31 - Deep Learning, Clinical Data Science and Radiology


May 23, 2017 10:00am ‐ May 23, 2017 12:00pm

Description

The purpose of this session is to explain what are machine and deep learning, their role in radiology research and practice, and how to prepare for them. This session will emphasize how radiologists can approach machine learning and deep learning, separating hype from reality. It will demonstrate how these self-improving algorithms will help radiologists, and the challenges of producing valid and useful computer models. Finally, it will present a roadmap for machine and deep learning in radiology, and ACR's roles as this technology evolves.

Learning Objectives
Upon completion of this session, participants will be able to:

  • Describe the basics of machine learning and deep learning.
  • Discuss the roles these software tools will play in radiology, and how they can help radiologists.
  • Identify what is needed to bring valid and useful machine and deep learning algorithms into widespread clinical practice, and ACR's roles as this technology evolves.

Speaker(s):

Disclosures

  • Garry Choy, MD : <p>Garry Choy, MD - This speaker has nothing to disclose</p>
  • Keith Dreyer, DO, PhD, FACR : <p>Keith Dreyer, DO, PhD, FACR - This speaker has nothing to disclose</p>
  • Raym Geis, MD, FACR : <p>Raym Geis, MD, FACR - Stock Options - (Spouse/Partner)Montage </p>

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