Clinical Decision Support
技能 已验证 活跃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.
To automate the creation of complex, evidence-based clinical documents for pharmaceutical research and clinical decision-making, ensuring accuracy and professional formatting.
功能
- Generates patient cohort analyses (biomarker-stratified)
- Creates treatment recommendation reports with GRADE grading
- Supports statistical analysis and visualization (survival curves, tables)
- Outputs publication-ready LaTeX/PDF documents
- Provides comprehensive guidance via reference files
使用场景
- Developing clinical practice guidelines with evidence synthesis
- Analyzing biomarker subgroups for drug development trials
- Creating treatment strategy documents for medical affairs
- Generating regulatory submission documentation
非目标
- Providing individual patient treatment plans for bedside care
- Replacing core clinical judgment or medical expertise
- Performing live data acquisition or real-time patient monitoring
工作流
- Define document type (cohort analysis, treatment recommendation)
- Provide relevant patient data (CSV) and biomarker information
- Specify document structure and formatting requirements
- Run Python scripts for data analysis, statistical calculations, and table generation
- Compile LaTeX output for final PDF document
- Review and refine document based on generated output and references
实践
- Evidence-based medicine
- Statistical rigor
- Regulatory compliance
- Publication standards
先决条件
- Python 3.7+
- Pandas
- NumPy
- Scipy
- Lifelines
- Matplotlib
- PyYAML (optional)
Execution
- info:Pinned dependenciesWhile Python dependencies are listed, they are not explicitly pinned with versions or lockfiles in the provided context.
- info:Pinned dependenciesPython dependencies are listed but not pinned with specific versions.
Maintenance
- info:Dependency ManagementDependencies are listed but not explicitly managed with lock files or vulnerability checks.
安装
npx skills add K-Dense-AI/claude-scientific-skills通过 npx 运行 Vercel skills CLI(skills.sh)— 需要本地安装 Node.js,以及至少一个兼容 skills 的智能体(Claude Code、Cursor、Codex 等)。前提是仓库遵循 agentskills.io 格式。
质量评分
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