medsci-project

Medical AI paper optimization for AI search engines (Perplexity, ChatGPT web, Elicit, Consensus, SciSpace) and RAG-based literature tools. Applies when drafting or reviewing titles, abstracts, structured summary boxes (Key Points / Research in Context / Plain-Language Summary), manuscripts for high-impact medical AI journals (Lancet Digital Health, Radiology, Radiology-AI, npj Digital Medicine, Nature Medicine), preprints (medRxiv/arXiv), GitHub README + CITATION.cff + Zenodo archives, and Hugging Face model/dataset cards. Integrates TRIPOD+AI, CLAIM 2024, STARD-AI, TRIPOD-LLM, DECIDE-AI reporting requirements with generative engine optimization (GEO) principles. Produces a visible pass/fail checklist.

Add a new journal to the MedSci Skills profile database. Extracts metadata from author guidelines, generates write-paper (detailed) and find-journal (compact) profiles in canonical format with quality gates.

Statistical analysis for medical research papers. Generates reproducible Python/R code with publication-ready tables and figures. Supports diagnostic accuracy, inter-rater agreement, meta-analysis, survival analysis, survey data, group comparisons, regression, propensity score, and repeated measures.

PubMed author profile analysis. Author name → PubMed fetch → study type classification → visualization → strategy report.

Generate N analysis scripts from a single methodology template × multiple exposure/outcome combinations. The "80-person team" pattern — same validated method, swap variables only. Produces batch R/Python code + summary matrix.