In this episode, hosts Mohannad, Prasanth, and Jason interview Teri Sippel Schmidt and Dr. Raym Geis about the Clinical Data Informatics initiative at SIIM. At its heart Clinical Data Informatics focuses on the use of tools such as Machine Learning algorithms, systems engineering, and medical imaging in sophisticated ways to derive insights and drive decision making for both clinical and business cases. Our guests introduce the series of videos developed in collaboration with SIIM. The discussion looks at the unique intersection of these disciplines and the need for a deep and broad understanding to create robust processes. Since January 2022, the team has provided educational videos from a curated group of CDI faculty to better understand the fundamentals of medical practice, imaging data, and data science.

Teri Sippel Schmidt is an Adjunct Professor at Johns Hopkins Medicine and Marquette University. She serves on multiple boards at SIIM. She is a frequent guest of the podcast and has been very active in the Hackathon Competition at the annual conference, serving as both team leader and mentor to aspiring imaging informaticists.

Raym Geis MD is a radiologist (semi-retired), interested in radiology data, standards, MLOps, and ethics of new data science approaches for medical imaging. He serves as Senior Scientist at the ACR Data Science Institute, Adjunct Associate Professor of Radiology at National Jewish Health, and Clinical Assistant Professor of Radiology at the University of Colorado School of Medicine. He is a member of the ACR Data Science Institute Advisory Group and the Canadian Association of Radiologists’ Artificial Intelligence Working Group, co-originator of the RSNA/SIIM National Imaging Informatics Curriculum and Course (NIIC-RAD). He was previously Chair of the Society for Imaging Informatics in Medicine (SIIM) and Vice-Chair of the ACR Informatics Commission and is a Fellow of both societies.

Information on the video series is available here.

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You can find us on Twitter: @SIIM_Tweets, and individually at @mohannadhussain, @jaynagels, @AliTejaniMD, @AAnandMD

Special Thanks to @RandalSilvey of for editing and post processing support.

Publish date

Jun 10, 2022


  • Clinical Data Informatics

Audience Type

  • Clinician
  • Developer
  • Imaging IT
  • Researcher/Scientist

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