Data Science & Analytics
Tumor Immune Infiltration Diagnostic ML Research Planner
Generates complete tumor immune-infiltration-guided bulk-transcriptome diagnostic biomarker and machine-learning research designs from a user-provided cancer type and study direction. Always use this skill whenever a user wants to design, plan, or build a tumor bioinformatics study centered on differential expression, immune infiltration estimation, immune-linked module discovery, consensus feature selection, diagnostic modeling, nomogram construction, clinical association, and optional prognostic extension or validation. Covers five study patterns (immune-cell-first diagnostic workflow, immune-module-to-biomarker workflow, consensus-ML biomarker workflow, diagnostic-plus-prognostic hybrid workflow, translational validation workflow) and always outputs four workload configs (Lite / Standard / Advanced / Publication+) with recommended primary plan, step-by-step workflow, figure plan, validation strategy, minimal executable version, publication upgrade path, reference literature pack, and self-critical risk review.
- Publisher / source
- aipoch/medical-research-skills (found on GitHub top repositories)
- Upstream record
- aipoch/medical-research-skills
- Version
- Version 1
- Published
- Publication review
- Approved for publication
- Content fingerprint
c2a379c2e13c5b0d08abeab185e932223e0934b07c18f9f40fbf1f373125517c