domains / families / research / clinical-decision-support

clinical-decision-support

combined

Generate 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). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug development, clinical research, and evidence synthesis. Prepares and validates research-only clinical decision-support evaluation, evidence-profile, cohort, survival, biomarker/model, privacy, and governance artifacts. Supports aggregate or synthetic research documentation and traceability, excluding patient care and live clinical operation.

When to use

• **Analyze patient cohorts** stratified by biomarkers, molecular subtypes, or clinical characteristics
• **Generate treatment recommendation reports** with evidence grading for clinical guidelines or pharmaceutical strategies
• **Compare outcomes** between patient subgroups with statistical analysis (survival, response rates, hazard ratios)
• **Produce pharmaceutical research documents** for drug development, clinical trials, or regulatory submissions
• **Develop clinical practice guidelines** with GRADE evidence grading and decision algorithms
• **Document biomarker-guided therapy selection** at the population level (not individual patients)
• **Synthesize evidence** from multiple trials or real-world data sources
• **Create clinical decision algorithms** with flowcharts for treatment sequencing

When not to use

• Individual patient treatment plans
• Bedside clinical care documentation

Skill page

Conflict

The K-Dense-AI copy is a distinct, safety-first procedure for generating research-only CDS evaluation and governance artifacts using local Python scripts and strict data gates. The other three copies (Vibe-Skills, aipoch, OpenClaw) are near-identical reproductions of a different skill focused on generating publication-ready LaTeX/PDF documents for pharmaceutical research, including specific formatting and statistical visualization instructions. Because the K-Dense copy provides a unique workflow (script-based validation, data gating, artifact headers) that the others lack, and the others provide unique content (LaTeX/PDF generation, specific pharma use cases) that the K-Dense copy lacks, crowning one would hide a real alternative approach to the same named skill.