The Radiology AI Handbook
The Radiology AI Handbook for Clinical Adoption is a 27-page field guide for imaging teams. It walks you through the whole life of an AI tool, from the first statement of the clinical problem to governance, evidence review, local testing, workflow integration, monitoring, and retirement.
What’s inside
- 13 focused chapters: clinical problem definition, understanding the tool, governance, evidence and local validation, workflow integration, meaningful human oversight, monitoring and incident response, privacy, security, fairness and regulation, value and change management, and a 90-day roadmap
- Ready-to-use tools: a one-page proposal template, vendor due-diligence questions, a local validation checklist, a launch readiness checklist, a monthly operational review agenda, and an example risk register
- Key takeaways at the start of each chapter, so you can skim first and read in depth later
- A glossary of the key terms, from automation bias to PPV, plus a referenced bibliography of regulatory and professional guidance
Who it’s for
- Radiologists and imaging leads evaluating AI tools
- Clinical informatics, IT, and quality and patient-safety teams
- Hospital and practice managers building an AI governance process
- Anyone preparing a proposal, pilot, or vendor review for imaging AI
It is vendor-neutral and doesn’t recommend or endorse any product. It focuses on process: how to ask better questions, test locally, keep humans meaningfully in the loop, and measure whether a tool earns its place in practice.
Format: PDF (27 Pages)
Important: This is an independent educational resource. It is not medical, legal, or regulatory advice and does not approve or validate any specific AI product. Regulatory requirements change, so verify current requirements in your jurisdiction.
License: Personal, non-transferable license for individual use. Resale, reposting, and redistribution are not permitted.