radiology-translation
radiology-translation is a Clinical knowledge & decision support skill for AI agents, published by huang-sir1 in the radiology-skills repository on GitHub. Skillspace rates radiology-translation C (71/100) and it passed the safety scan; the rating is based on static analysis only.
Move a validated imaging model from retrospective performance toward clinical use — design the clinical-use scenario, model outputs, reader (multi-reader multi-case) studies of radiologist-vs-AI-vs-radiologist+AI, decision thresholds tied to actions, net-benefit/decision-curve framing, prospective and real-world validation, and PACS/RIS workflow integration. Use when the user wants a reader study, clinician+AI gain, prospective/real-world validation, deployment plan, "临床转化/读者研究/前瞻性验证", or to know what it takes to claim clinical utility. Produces a translation plan with the use scenario, reader-study design, threshold-to-action mapping, and prospective/workflow design. Never lets a retrospective AUC be reported as clinical readiness.
- Grade
- C
- Quality
- 71 / 100
- Safety
- Passed
- GitHub stars
- 819
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 94 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
- Scope
- Portable: works in any project. generic methodology for clinical validation of imaging models
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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