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clinical-decision-support

Generate publication-ready clinical decision support documents from biomarker-driven cohorts.

321|26|Updated Mar 10, 2026
Search Tags:#latex#publication#evidence-synthesis#cds#biomarkers#clinical-decision-support#regulatory-submissions
One-click install
npx skills add https://github.com/mkurman/tamux --skill clinical-decision-support-mkurman
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: clinical-decision-support
Source: https://github.com/mkurman/tamux/tree/main/skills/scientific-skills/clinical-decision-support
Command: npx skills add https://github.com/mkurman/tamux --skill clinical-decision-support-mkurman

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, numpy, scipy, lifelines, matplotlib, scikit-learn, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

Generates professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, enabling population-level analyses, evidence synthesis, and guideline development with publication-ready LaTeX/PDF outputs.

Core Features & Use Cases

  • Biomarker-driven cohort analyses with GRADE-based recommendations
  • Treatment guidance reports and regulatory-submission-ready documents
  • Publication-ready outputs (LaTeX/PDF) with integrated figures and tables
  • Use Case: Generate a biomarker-stratified cohort report and a concurrent treatment recommendation guideline

Quick Start

To begin, provide a biomarker-defined cohort and request a CDS report.

Frequently Asked Questions about clinical-decision-support

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate publication-ready clinical decision support documents from biomarker data?▼

Publication-ready clinical decision support documents are generated by providing a biomarker-defined cohort to trigger template-driven LaTeX/PDF outputs, integrating GRADE-based evaluation, statistical methods, figures, and tables automatically.

Can I create regulatory submission documents with GRADE-based evidence synthesis using Python?▼

Yes, regulatory submission documents are produced using template-driven scripts that enforce GRADE-based evaluation, structured reporting, and reproducible statistical methods to yield submission-ready LaTeX/PDF outputs.

What's the best way to automate cohort analysis and treatment recommendation reports for pharmaceutical research?▼

Automating cohort analysis and treatment recommendation reports involves supplying biomarker-driven cohort data to predefined templates, which then execute statistical analysis and populate publication-grade LaTeX documents.

Does this clinical decision support workflow require specific Python dependencies like pandas and lifelines?▼

Yes, the clinical decision support workflow requires Python dependencies including pandas, numpy, scipy, lifelines, matplotlib, and scikit-learn to perform reproducible statistical analysis and generate integrated figures.

How do I produce LaTeX tables and figures for biomarker-stratified cohort reports?▼

LaTeX tables and figures for biomarker-stratified cohort reports are produced automatically through template scripts that process cohort data and generate publication-ready visualizations integrated directly into the final PDF.

When should I use automated CDS document generation instead of manual clinical guideline authoring?▼

Automated CDS document generation should be used when population-level biomarker analyses, evidence synthesis, or regulatory documentation require reproducible statistical methods, GRADE-based evaluation, and structured publication-ready outputs.

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