AI-Assisted Medical Diagnostic Assurance Course

Name: AI-Assisted Medical Diagnostic Assurance Course
Availability: InStock

Govern diagnostic AI use, evidence, performance, human review, workflow controls, incidents, monitoring, and change.

At a glance

Duration: 5 days
Format: Classroom
Cities: Langkawi, Tashkent, Amsterdam, Al Jubail, Dubai, Phuket and more
Next session: 11 – 15 October 2026, Langkawi
Average fee: 5,800 €

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AI-Assisted Medical Diagnostic Assurance Course

Overview

AI-Assisted Medical Diagnostic Assurance Course is a five-day course for diagnostic service managers, laboratory and imaging operations personnel, clinical quality teams, health informatics personnel, and diagnostic governance staff, who leave with an AI Diagnostic Assurance File. Participants define intended use, trace data provenance, review performance and subgroup evidence, place human checkpoints, integrate controls into workflows, and manage incidents, monitoring, and changes. Agile Leaders Training Center provides training in AI-assisted medical diagnostic assurance.

Who Should Attend

Diagnostic service personnel responsible for safe adoption, resources, and operational oversight
Laboratory operations personnel responsible for diagnostic workflows, evidence, and quality controls
Imaging operations personnel responsible for interpretation workflows, handoffs, and performance review
Clinical quality personnel responsible for patient safety, incidents, corrective actions, and assurance
Health informatics personnel responsible for integration, data lineage, access, and monitoring
Governance personnel responsible for intended use, human authority, risk decisions, and change approval

The course assumes participants support diagnostic services or their governance, and it leaves out independent diagnosis, clinical treatment decisions, model development, coding, and advanced biostatistics.

Departments and Industries

The course supports diagnostic AI assurance across healthcare providers, diagnostic networks, technology suppliers, and assurance functions.

Medical imaging and radiology operations
Laboratory medicine and pathology services
Clinical quality and patient safety
Health informatics and digital health
Medical technology operations
Risk, privacy, and internal assurance

Learning Objectives

By the end of this course, participants will be able to:

Diagnose diagnostic AI use cases and intended-use boundaries
Analyze data provenance and reference-standard evidence
Evaluate performance measures and subgroup variation
Build human review and workflow integration controls
Apply incident, monitoring, and change-control methods
Build an AI Diagnostic Assurance File

Course Agenda

Day 1: Use Cases and Intended Use

Diagnostic AI Use-Case Definition Canvas
Intended-Use and Exclusion Boundary Statement
Patient, User, and Setting Context Map
Diagnostic Harm and Benefit Scenario Register
Human Authority and Accountability Charter

Day 2: Data and Reference Evidence

Diagnostic Data Provenance Map
Reference Standard Selection Record
Data Quality and Missingness Checklist
Population Representation and Subgroup Matrix
Privacy and Minimum-Data Control Sheet

Day 3: Performance and Human Review

Diagnostic Performance Measure Definition Sheet
Threshold and Error Tradeoff Table
Subgroup Performance Comparison Grid
Human Review and Override Decision Tree
Evidence Limitation and Uncertainty Log

Day 4: Workflow, Incidents, and Change

Diagnostic Workflow Integration and Handoff Map
AI Output Verification Checkpoint Design
Diagnostic Incident and Escalation Record
Performance Monitoring and Drift Dashboard
Change Request and Reassurance Gate

Day 5: Diagnostic Assurance Practice

Suggested Exercise: Define Intended Use and Diagnostic Boundaries
Suggested Exercise: Audit Data and Reference Evidence
Suggested Exercise: Review Performance and Subgroup Variation
Suggested Exercise: Map Workflow, Incident, and Change Controls
Capstone Exercise: AI Diagnostic Assurance File

Practical Exercises

The course uses suggested activities that turn diagnostic AI evidence into controlled operational assurance artifacts.

Suggested activity: define a diagnostic use case, exclusions, affected parties, foreseeable harms, and accountable human authority
Suggested activity: trace data origins, select reference evidence, inspect missingness and representation, and apply minimum-data controls
Suggested activity: compare performance measures, thresholds, error tradeoffs, subgroup results, overrides, and uncertainty
Suggested activity: map an imaging or laboratory workflow, place checkpoints, record an incident, and define monitoring and change gates

FAQs

Who suits AI-assisted medical diagnostic assurance, and what does the course assume?

AI-assisted medical diagnostic assurance suits diagnostic operations, quality, informatics, and governance personnel. The course assumes experience supporting diagnostic services or their controls.

How does medical diagnostic assurance differ from clinical diagnosis training?

Medical diagnostic assurance governs intended use, evidence, performance, oversight, workflows, incidents, monitoring, and change, while clinical diagnosis training develops professional examination and diagnostic reasoning.

How should diagnostic AI performance be reviewed?

Diagnostic AI performance should be reviewed against defined measures, thresholds, reference evidence, error consequences, relevant populations, subgroup variation, workflow conditions, uncertainty, and accountable human judgment.

Why does diagnostic AI require human review and override controls?

Human review and override controls keep accountable professionals able to question outputs, recognize missing context, compare other evidence, stop unsafe use, document decisions, and escalate concerns.

What belongs in an AI Diagnostic Assurance File?

The file should contain intended use, exclusions, context, data provenance, reference evidence, performance and subgroup reviews, human controls, workflow checkpoints, incidents, monitoring, changes, approvals, and corrective actions.

Conclusion

Participants take back an AI Diagnostic Assurance File linking intended use, data, reference evidence, performance, subgroup checks, human authority, workflows, incidents, monitoring, and changes. It changes how diagnostic teams move from informal adoption to traceable operational assurance. The file supports accountable review, escalation, approval, and continuing control.

credits: 5 credit per day

Course Mode: full-time

Provider: Agile Leaders Training Center

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Showing 1-20 of 76 events

Location	Dates	Duration	Mode	Price
Langkawi	Week 41, 2026 11 – 15 October 2026	5 Days	Onsite	€6,000
Tashkent	Week 42, 2026 18 – 22 October 2026	5 Days	Onsite	€4,500
Amsterdam	Week 43, 2026 19 – 23 October 2026	5 Days	Onsite	€5,700
Al Jubail	Week 43, 2026 25 – 29 October 2026	5 Days	Onsite	€5,700
Dubai	Week 44, 2026 26 – 30 October 2026	5 Days	Onsite	€4,500
Phuket	Week 44, 2026 1 – 5 November 2026	5 Days	Onsite	€6,000
Paris	Week 46, 2026 9 – 13 November 2026	5 Days	Onsite	€5,700
Milan	Week 47, 2026 16 – 20 November 2026	5 Days	Onsite	€5,700
Abu Dhabi	Week 47, 2026 16 – 20 November 2026	5 Days	Onsite	€4,700
Chicago	Week 47, 2026 22 – 26 November 2026	5 Days	Onsite	€12,000
Doha	Week 48, 2026 29 November – 3 December 2026	5 Days	Onsite	€5,500
Sharm El-Sheikh	Week 50, 2026 7 – 11 December 2026	5 Days	Onsite	€4,100
Cairo	Week 51, 2026 14 – 18 December 2026	5 Days	Onsite	€4,100
Vienna	Week 51, 2026 14 – 18 December 2026	5 Days	Onsite	€5,700
Dubai	Week 52, 2026 21 – 25 December 2026	5 Days	Onsite	€4,500
London	Week 52, 2026 21 – 25 December 2026	5 Days	Onsite	€5,700
Rome	Week 53, 2026 28 December 2026 – 1 January 2027	5 Days	Onsite	€5,700
Cape town	Week 53, 2027 3 – 7 January 2027	5 Days	Onsite	€4,500
Cairo	Week 02, 2027 11 – 15 January 2027	5 Days	Onsite	€4,100
Singapore	Week 02, 2027 11 – 15 January 2027	5 Days	Onsite	€5,700

Frequently asked questions

What does this course cover?

OverviewAI-Assisted Medical Diagnostic Assurance Course is a five-day course for diagnostic service managers, laboratory and imaging operations personnel, clinical quality teams, health informatics personnel, and diagnostic governance staff, who leave with an AI Diagnostic Assurance File. Participants define intended use, trace data provenance, review per…

Are training dates available?

Yes. Available dates and destinations are listed in the course dates section on this page.

How can I register?

Choose an available date on this page and complete the registration form, or send a programme enquiry.

Can I download the course brochure?

Yes. Use the brochure download link provided on this page.

AI-Assisted Medical Diagnostic Assurance Course