Edward Pettyjohn, M.D.

Diagnostic Radiology Resident
University of Illinois College of Medicine Peoria (UICOMP)

Poster(s):

• A Radiology M&M-Style Root-Cause Analysis Framework for Artificial Intelligence Errors: Development of a Six-Domain Taxonomy

• Advocating for Open-Access Imaging Datasets: Building the Foundation for Transparent and Reproducible AI Innovation

• Algorithmic Drift and Lifecycle Quality Assurance in Radiology AI: A Framework for Ongoing Performance Monitoring and Re-Validation

• Bridging the AI Divide: Policy Pathways for Equitable Access to Imaging AI Across Academic and Community Settings

• Closing the Regulatory Gap: A National Policy Framework for Transparent and Reproducible Radiology AI

• Cost-Efficiency Through Reproducibility: The Hidden Economics of Transparent AI Workflows in Radiology

• Credentialing the Algorithm: A Framework for Institutional Oversight of Clinical AI Systems in Radiology

• From ROC to Report: A Framework for Safely Communicating AI-Derived Probability and Uncertainty in Radiology

• Preventing Silent Model Drift: A Reproducibility Governance Framework for Radiology Leadership

• Reproducibility = Safety: Establishing Transparent Validation as a Quality Metric for Radiology AI

• Teaching Clinical AI Literacy: An Educational Framework for Communicating Risk and Uncertainty in Radiology

• Teaching Radiology Trainees to Recognize AI Failure Modes: A Six-Domain Educational Framework