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SIIM26 logo footer
  • Attend
    • Hotels + Venue
    • Who Should Attend?
    • Networking Events
    • Justify Your Attendance!
    • Preliminary Program
    • FAQs
  • Program
    • Program Agenda
    • Featured Education
      • General Sessions
      • Learning Labs
      • Scientific Presentations
      • SMIT Picks & Tips
      • Ask the Informaticists Meetups
    • Roadmaps
      • Cardiology
      • Dermatology
      • Ophthalmology
      • Pathology
      • Radiology
      • SMIT Picks & Tips
    • Expo Learning
    • Continuing Education
    • Speakers List
    • Preliminary Program
    • Speaker Resources
  • TECH Expo
    • Exhibitors
    • Alphabetical Exhibitor List
    • Product Categories
    • Expo Learning
    • Floor Plan
  • Pre-Conference
    • Epic Users Group Meeting
    • SIIM-ACR Data Science Summit
  • Exhibit + Sponsor
    • How To Sign Up
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    • Startup Street
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Spaeth-Cook-Douglas
Event Speaker

Douglas Spaeth-Cook, DO, MSPH

Resident Physician
Emory University Hospital

Douglas Spaeth-Cook, DO, MSPH, is a radiology resident at Emory University in the Integrated Imaging Informatics track (I3T). He has a background in biomedical informatics, having earned a Master of Science in public health while focusing on translational research involving live-cell imaging of 3D in vitro tumor models for peritoneal spread of ovarian carcinoma. His current interests center on operational and workflow informatics, with a goal of improving healthcare efficiency and engagement for patients, clinicians, and radiologists.

Sessions

Artificial Intelligence in Radiology Residency Training

Presented by Douglas Spaeth-Cook, DO, MSPH, Peter Chang, MD , Margaret Lin, MD, Morgan P. McBee, MD, CIIP in Radiology Jun 12, 2026 | 2:00 PM.

As artificial intelligence becomes increasingly embedded in radiology workflows, residency programs face growing pressure to prepare trainees not only to use AI tools, but to critically evaluate them. Future radiologists need a practical understanding of model performance, output interpretation, bias, validation, and clinical limitations in order to make informed decisions in AI-enabled environments.  This session examines how…

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