design-study

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Study design and validity review for radiology and medical AI research. Identifies analysis unit, cohort logic, leakage risks, comparator design, validation strategy, and reporting guideline fit before drafting or submission.

Web & Frontend 220 stars 55 forks Updated today MIT

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Skill Content

# Design-Study Skill ## Purpose This skill pressure-tests whether a study is answerable, interpretable, and defensible before large amounts of drafting or analysis work accumulate. Use it when: - a study question is known but the analysis plan is still fluid - the user wants a methods sanity check - a manuscript feels vulnerable to reviewer criticism - a peer review requires explicit methodological diagnosis --- ## Communication Rules - Communicate with the user in their preferred language. - Use English for statistical, radiologic, and reporting-guideline terminology. - Be direct about validity risks, but always propose the smallest feasible fix first. --- ## Core Review Questions Always inspect these dimensions: 1. What is the exact research question? 2. What is the analysis unit: patient, lesion, exam, study, phase, report? 3. What is the index date or decision point? 4. How are inclusion and exclusion criteria applied? 5. Is there any information leakage? 6. What is the reference standard or endpoint definition? 7. What comparator is clinically meaningful? 8. What validation strategy is used? 9. What uncertainty reporting is required? 10. Which reporting guideline best fits? 11. Are exposure/outcome/covariate **definitions literature-grounded**, or invented ad-hoc from the data dictionary? If ad-hoc, defer to `/define-variables` before drafting Methods. --- ## Standard Output ```text ## Study Design Review Question: ... Study type: ... Analysis unit: ... Inde...

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Author
Aperivue
Repository
Aperivue/medsci-skills
Created
3 months ago
Last Updated
today
Language
Python
License
MIT

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