model-evaluation

Use when clinical data may contain PHI and must be de-identified before any LLM-assisted analysis.

Use when designing a study that benchmarks AI systems against a human-expert panel, before data collection.

Use when sending local changes back to the project (an added journal profile, a fixed checklist item, an adapted skill) or reporting a false positive or bug.

Use when exposure, outcome, covariate or eligibility definitions and cutoffs need a citable basis before the protocol.

Use when a target journal has no profile yet.

Use when planning how many patients or cases a study needs before data collection (power analysis, IRB justification).

Use when writing a literature review article (narrative, scoping PRISMA-ScR or systematic).

Use when analyzing a researcher's publication record from PubMed.

Use when a medical AI paper should be found and cited by AI search engines and RAG tools.

Use when auditing a manuscript item by item against a reporting guideline or risk-of-bias tool.

Use when a clinical CSV/Excel dataset needs profiling and cleaning before analysis (missing values, outliers, duplicates, type mismatches).

Use when checking a radiology or medical AI study design before drafting or submission.