Intended Participants
Digital health teams, imaging professionals, healthcare innovation managers
Learning Objectives
Assess realistic AI opportunities, evaluate data and implementation risks, and produce an actionable and responsible adoption plan.
Delivery Format
Instructor-led seminars, case workshops, guided exercises, and applied capstone; online, hybrid, or in-person by arrangement.
Curriculum · Six Instructional Units
- Digital health systems, diagnostic AI landscape, and clinical workflow
- Imaging datasets, annotation, representativeness, and governance
- Sensitivity, specificity, external validation, and error analysis
- Workflow integration, clinician review, and patient safety
- Procurement, regulatory considerations, cybersecurity, and monitoring
- Capstone: diagnostic AI deployment readiness assessment
Applied Program Outcome
Diagnostic AI readiness checklist and validation plan
Assessment
Participation and case exercises (30%); applied project (40%); final presentation and reflection (30%).
Institutional Customization
Examples, cases, timetable, and institutional priorities may be tailored after needs assessment.
Important: This is a proposed Beyond Academic curriculum, not a confirmed university or hospital offering. Any certificate or continuing education credit is subject to separate written confirmation; none is guaranteed. AI content is educational; clinical decisions remain with qualified professionals and authorized institutions.