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clinical-decision-support

Generate clinical decision support documents with LaTeX/PDF outputs.

Updated Feb 3, 2026
Search Tags:#latex#clinical decision support#biomarker analysis#treatment guidelines#pharmaceutical research#grade system
One-click install
npx skills add https://github.com/loganylchen/skills --skill clinical-decision-support-loganylchen
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: clinical-decision-support
Source: https://github.com/loganylchen/skills/tree/main/clinical-decision-support
Command: npx skills add https://github.com/loganylchen/skills --skill clinical-decision-support-loganylchen

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill automates the creation of professional, evidence-based clinical decision support (CDS) documents, streamlining the process for pharmaceutical companies, researchers, and medical decision-makers.

Core Features & Use Cases

  • Automated Document Generation: Creates publication-ready LaTeX/PDF documents for patient cohort analyses and treatment recommendation reports.
  • Evidence-Based Synthesis: Integrates biomarker data, statistical analysis, and GRADE grading for robust clinical insights.
  • Use Case: Generate a comprehensive report analyzing a new drug's efficacy in a specific patient subgroup, complete with survival curves, forest plots, and GRADE-graded treatment recommendations for a medical society guideline.

Quick Start

Generate a patient cohort analysis for 45 NSCLC patients stratified by PD-L1 expression receiving pembrolizumab, including ORR, median PFS, median OS with hazard ratios comparing PD-L1 ≥50% vs <50%, and generate Kaplan-Meier curves and a waterfall plot.

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 a clinical decision support document with biomarker-stratified analysis?▼

You generate clinical decision support documents by inputting patient cohort parameters and biomarker expressions to receive automated patient stratification, statistical outcome comparisons, and publication-ready LaTeX/PDF reports with evidence-based treatment recommendations.

What is GRADE system integration for treatment recommendation reports?▼

GRADE system integration in treatment recommendation reports evaluates biomarker-stratified statistical outcomes to grade clinical evidence quality, producing robust insights for pharmaceutical researchers and medical decision-makers.

Can I create Kaplan-Meier curves and forest plots for patient cohort analysis in LaTeX?▼

Yes, patient cohort analysis generates publication-ready LaTeX/PDF outputs containing Kaplan-Meier curves, waterfall plots, and forest plots visualizing statistical hazard ratios for biomarker-stratified groups.

Does clinical decision support generation work for pharmaceutical research and medical society guidelines?▼

Clinical decision support generation works for pharmaceutical research and medical society guidelines by analyzing drug efficacy in patient subgroups and outputting GRADE-graded treatment recommendations suitable for medical guideline integration.

What statistical outcomes are needed to compare biomarker-stratified patient groups?▼

Comparing biomarker-stratified patient groups requires statistical outcomes including ORR, median PFS, median OS, and hazard ratios to calculate efficacy differences between biomarker expression thresholds.

What limitations exist when automating clinical decision support document generation?▼

Automating clinical decision support document generation requires pre-structured biomarker data and statistical inputs, synthesizing provided GRADE grading and patient cohort parameters rather than autonomously conducting raw clinical trial statistical analysis.

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