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SIIM26 logo footer
  • Attend
    • Hotels + Venue
    • Who Should Attend?
    • Networking Events
    • Justify Your Attendance!
    • Preliminary Program
  • Program
    • Program Agenda
    • Featured Education
      • General Sessions
      • Learning Labs
      • Scientific Presentations
      • SMIT Picks & Tips
    • 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
    • Sponsor + Advertise
    • Startup Street
    • Booth Contract
    • Rules & Regulations
    • Vendor Prospectus
    • Exhibitor Resources
    • Suitcase Marketing & Unauthorized Research Policy
  • Register
John Giannini, PhD, speaking at the SIIM Annual Meeting, focusing on medical imaging innovation and healthcare technology advancements.
Event Speaker

John Giannini, PhD

Health Science Policy Analyst
All of Us Research Program, National Institutes of Health

John Giannini serves as Branch Chief of the Data Systems Branch at the All of Us Research Program, where he leads strategy for expanding high-value research data, including medical imaging and electronic health record resources. Trained as a physicist and optical engineer, he brings expertise in fluorescence microscopy, retinal imaging, and quantitative image analysis from doctoral and postdoctoral research. At All of Us, he advances data quality frameworks and guides acquisition planning for new imaging and linked data types that strengthen the program’s utility for researchers. His work focuses on building scalable data infrastructure to support diverse, data-driven biomedical discovery.

Sessions

Ophthalmic Imaging AI: Computer Vision for Retinal Disease Prediction

Presented by Kerry E. Ashby, MS, John Giannini, PhD, Syed Haqqani, MS, Amberlynn Reed, MPH in Ophthalmology, Radiology Jun 10, 2026 | 1:45 PM.

Artificial intelligence is rapidly expanding the diagnostic value of ophthalmic imaging, transforming retinal photographs and optical coherence tomography (OCT) scans into rich sources of predictive clinical insight. As deep learning and computer vision methods mature, retinal imaging is increasingly being used not only to document ocular abnormalities, but also to identify subtle biomarkers associated with progressive diseases…

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