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Issued to

Abigail Turok

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Credential Verification

Issue date: June 11, 2026

ID: bb5666e3-15c9-477b-9a1f-907d8ea42d47

Issued by

Walter Reed National Military Medical Center Diagnostic Radiology Residency Program

The Diagnostic Radiology Residency at Walter Reed National Military Medical Center (WRNMMC) is a 4-year, ACGME-accredited, military, tri-service GME program.

Type

Course

Level

Foundational

Format

Hybrid

Duration

13 hours

Price

Free

Description

This credential verifies the successful completion of the Fundamentals of AI in Radiology with Capstone course. It signifies that the earner—whether a Radiology resident, faculty member, or staff—understands the foundational concepts, applications, and responsible use of Artificial Intelligence across Radiology practice, research, administration, and education. Through hands-on exploration of AI tools and a culminating capstone project, the earner has developed the required skills to effectively and ethically integrate AI into modern Radiology workflows.

Skills

Prompt Engineering

Machine Learning

Artificial Intelligence Ethics

Responsible Artificial Intelligence Use

Artificial Intelligence Development

Artificial Intelligence

Artificial Intelligence Tool Evaluation

Large Language Models

Radiology Artificial Intelligence Integration

Earning Criteria

Test

Pre- and Post-Course Surveys/Tests

Participation

Participating in all nine hybrid sessions synchronously or asynchronously: 1. Introduction to AI Technologies and Their Ethical Use 2. Mastering Accurate and Effective Radiology Prompt Engineering 3. The Evolution of AI in Medical Imaging 4. Practical Applications of AI in Modern Radiology Workflows 5. Exploring AI‑Driven Image and Video Tools for Radiology 6. A Practical AI Evaluation Playbook 7. Frontiers in Radiology AI Research 8. AI Simulation in Radiology 9. AI Capstone Presentations

Participation

Participate in an agentic AI patient simulation activity and post-experience survey.

Assignment

Each participant completed a culminating project demonstrating applied understanding of AI concepts and tools. The project was an original, meaningful product that has potential value for Radiology education, clinical workflow, research, or administration.