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clinical-decision-support

Generate publication-ready clinical decision support documents with GRADE grading and survival analyses.

1|Updated Mar 11, 2026
Search Tags:#guidelines#latex#evidence-synthesis#cds#biomarkers#clinical-decision
One-click install
npx skills add https://github.com/SciMate-AI/scicli --skill clinical-decision-support-scimate-ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: clinical-decision-support
Source: https://github.com/SciMate-AI/scicli/tree/main/internal/skills/bundled/claude-scientific-skills/skills/clinical-decision-support
Command: npx skills add https://github.com/SciMate-AI/scicli --skill clinical-decision-support-scimate-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, numpy, scipy, lifelines, matplotlib, pyyaml, 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, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Outputs publication-ready LaTeX/PDF reports and supports GRADE grading, statistical analyses (hazard ratios, survival curves, waterfall plots), and regulatory compliance.

Core Features & Use Cases

  • Population-level cohort analyses with biomarker stratification to inform regulatory submissions
  • Evidence-based treatment recommendation reports with GRADE grading and decision algorithms
  • Publication-ready outputs in LaTeX/PDF, with integrated figures and tables
  • Template-driven document generation using bundled assets, references, and scripts
  • Use Case: Generate a biomarker-guided cohort analysis and a corresponding treatment guideline document for a cancer subtype

Quick Start

Create a treatment recommendation report for a biomarker-defined cancer cohort with GRADE grading.

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 for regulatory submissions?▼

You can generate publication-ready clinical decision support documents by running cohort analyses and evidence-synthesis workflows that output LaTeX/PDF reports with integrated figures, GRADE grading, and hazard ratios.

Can I create biomarker-stratified survival curves and waterfall plots for patient cohort analyses?▼

Yes, this skill performs population-level cohort analyses with biomarker stratification, producing statistical outputs like survival curves and waterfall plots to inform pharmaceutical research and regulatory submissions.

How do I build evidence-based treatment guidelines with GRADE grading and decision algorithms?▼

You can build evidence-based treatment guidelines by applying GRADE grading and generating TikZ-based decision algorithms within template-driven LaTeX/PDF reports for clinical decision support.

Do I need a LaTeX environment to produce GRADE-graded clinical decision support reports?▼

Yes, generating publication-ready clinical decision support documents requires a LaTeX environment to compile the template-driven outputs, integrated statistical figures, and decision algorithms into a final PDF.

What's the best way to analyze a biomarker-defined cancer cohort for a treatment recommendation report?▼

The best way is to use evidence-synthesis workflows that apply biomarker stratification to patient cohorts, calculate statistical outcomes, and generate a publication-ready treatment guideline document with GRADE grading.

Does this clinical decision support skill support survival analysis with hazard ratios and lifelines?▼

Yes, the skill uses the lifelines dependency alongside pandas and scipy to calculate hazard ratios and generate survival curves for population-level clinical decision support document generation.

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