clinical-decision-support

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

4|1|Updated Apr 8, 2026

Search Tags:#guidelines #latex #cohort-analysis #evidence-synthesis #tikz #clinical-decision-support #grade

Ready to run

npx skills add https://github.com/ARAVINDAN20/Claude-Research-Paper-OS --skill clinical-decision-support-aravindan20

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: clinical-decision-support
Source: https://github.com/ARAVINDAN20/Claude-Research-Paper-OS/tree/main/.claude/skills/claude-scientific-writer/.claude/skills/clinical-decision-support
Command: npx skills add https://github.com/ARAVINDAN20/Claude-Research-Paper-OS --skill clinical-decision-support-aravindan20

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Generate publication-ready clinical decision support (CDS) documents from cohort analyses, evidence synthesis, and biomarker-guided recommendations.

Core Features & Use Cases

Biomarker-based patient cohort analyses (OS, PFS, ORR) with stratification and statistics
Evidence-based treatment recommendation reports with GRADE grading and decision algorithms
Guidelines-aligned outputs in LaTeX/PDF and TikZ diagrams for clinical pathways
Templates, templates integration, reproducibility, and HIPAA-compliant reporting

Quick Start

Open Claude Code in a project with a dataset of 60 HER2+ metastatic breast cancer patients and run a CDS report using the built-in templates.

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 cohort analysis data?▼

To generate clinical decision support documents from cohort analysis, this Skill automates report creation using patient stratification and survival statistics. It produces publication-ready outputs with GRADE grading and LaTeX formatting directly from your analytical data.

Can I create GRADE-graded treatment recommendations and decision algorithms automatically?▼

Yes, you can create GRADE-graded treatment recommendations automatically. This Skill applies evidence synthesis and biomarker-guided cohort stratification to generate clinical decision algorithms and recommendation reports aligned with reproducible standards.

Does this Skill support LaTeX and TikZ outputs for clinical pathway guidelines?▼

This Skill fully supports LaTeX and TikZ outputs for clinical pathway guidelines. It integrates with existing templates and references to satisfy reproducible document standards, producing structured PDF reports and visual pathway diagrams.

How do I perform biomarker-based patient cohort analysis for OS, PFS, and ORR metrics?▼

Biomarker-based patient cohort analysis for OS, PFS, and ORR is processed using pandas, numpy, and scipy. The Skill stratifies patient populations, calculates survival statistics, and formats results into reproducible HIPAA-compliant reports.

What data formats do I need for cohort-based clinical decision support reporting?▼

Cohort-based clinical decision support reporting requires structured patient datasets, typically JSON or CSV files readable by pandas. The environment needs Python dependencies like scikit-learn and scipy to execute statistical analysis and template integration.

Are there limitations when generating clinical decision support documents for large patient cohorts?▼

Limitations for generating clinical decision support documents depend on your Python environment's capacity to handle large pandas datasets. While it processes biomarker stratification and GRADE grading, extremely large cohorts may require optimized data pipelines before document generation.