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clinical-decision-support

Generate LaTeX/PDF clinical decision support documents from biomarker and outcome evidence.

Updated Jul 1, 2026
Search Tags:#survival analysis#cohort analysis#clinical decision support#biomarker stratification#grade evidence#tikz flowcharts
One-click install
npx skills add https://github.com/jasrajtulsi/GRAD-SCOPE --skill clinical-decision-support-jasrajtulsi
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: clinical-decision-support
Source: https://github.com/jasrajtulsi/GRAD-SCOPE/tree/main/.claude/skills/clinical-decision-support
Command: npx skills add https://github.com/jasrajtulsi/GRAD-SCOPE --skill clinical-decision-support-jasrajtulsi

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill turns complex clinical and pharmaceutical evidence into polished decision-support documents, removing the manual work of assembling biomarker tables, survival analyses, guideline summaries, and publication-ready layouts.

Core Features & Use Cases

  • Patient cohort analysis: Stratify cohorts by biomarkers, molecular subtypes, demographics, or treatment exposure and summarize outcomes such as ORR, PFS, OS, and safety.
  • Treatment recommendation reports: Draft evidence-based clinical guidance with GRADE ratings, monitoring guidance, and decision algorithms.
  • Scientific visuals and tables: Produce Kaplan-Meier curves, forest plots, waterfall plots, cohort tables, and TikZ pathway diagrams for LaTeX/PDF reports.
  • Use cases: Ideal for pharmaceutical strategy documents, translational research summaries, guideline development, and biomarker-driven clinical reporting.

Quick Start

Ask the skill to generate a biomarker-stratified cohort analysis or GRADE-based treatment recommendation report for your disease area and include the figures, tables, and LaTeX-ready output.

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 publication-ready clinical decision support report from patient cohort data?▼

To generate a clinical decision support report, input patient biomarker and outcome data to produce stratified cohort tables, GRADE evidence ratings, Kaplan-Meier curves, and LaTeX/PDF formatted documents with validation checks.

How does biomarker stratification work for survival analysis in clinical research?▼

Biomarker stratification for survival analysis works by grouping patient cohorts by molecular subtypes or biomarkers, then calculating outcomes like PFS and OS to produce Kaplan-Meier curves and forest plots using lifelines and scipy.

Can I use pandas and lifelines to create GRADE evidence-based treatment recommendations?▼

Yes, you can use pandas and lifelines alongside clinical guidelines to draft GRADE-graded treatment recommendations, generating decision algorithms and monitoring guidance formatted for LaTeX/PDF publication.

Does this clinical decision support tool produce TikZ flowcharts for treatment pathway design?▼

Yes, this clinical decision support tool produces TikZ flowcharts to visualize treatment pathways, alongside waterfall plots and cohort tables, formatting them into LaTeX-ready PDF outputs with compliance checks.

What is the best way to summarize clinical trial outcomes like ORR and PFS for pharmaceutical strategy documents?▼

The best way to summarize clinical trial outcomes is to stratify patient cohorts by treatment exposure, calculate ORR and PFS metrics, and output publication-ready summary tables and figures for pharmaceutical strategy documents.

Do I need scikit-learn and matplotlib installed to run survival analysis and generate cohort tables?▼

Yes, you need scikit-learn and matplotlib installed along with pandas, numpy, scipy, and lifelines to execute survival analysis, generate visual cohort tables, and render publication-ready clinical decision support outputs.

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