clinical-decision-support

To generate publication-ready clinical decision support reports, describe your disease state and select a cohort analysis or guideline workflow. The process outputs LaTeX/PDF documents with integrated references, TikZ diagrams, and GRADE evidence synthesis for regulatory submissions.

Yes, you can perform Kaplan-Meier survival analysis and population-level cohort analyses with biomarker stratification. The workflow utilizes lifelines and scipy to process clinical data and generate survival curves for treatment-recommendation reports.

Creating GRADE evidence synthesis documents involves integrating survival analysis and decision algorithms into the workflow. The system uses lifelines for Kaplan-Meier curves and GRADE grading to produce evidence-synthesis reports for medical affairs.

Yes, the clinical decision support workflow outputs publication-ready LaTeX/PDF documents. It automatically integrates TikZ flowcharts and tables to visualize decision algorithms and cohort analysis data for pharmaceutical research.

For cohort analysis and evidence synthesis, you need tabular data formats compatible with pandas and numpy. The workflow processes clinical datasets to perform biomarker-guided treatment recommendations and population-level analyses.

Limitations include dependency on Python environments with scipy, lifelines, and matplotlib for generating survival analyses and plots. The workflow is specialized for pharmaceutical research and clinical practice GRADE grading, not general document creation.