Public demo case

Heart Failure Cox Regression Demo Case

This public example shows the kind of reviewable output data2paper.ai can prepare: data profiling, Table 1, Kaplan-Meier curves, Cox regression, forest plots, number checks, and reproducibility materials.

This case is a demonstration using public example data. It is not clinical advice, not a publication guarantee, and not a claim that any particular analysis is suitable for every heart failure study. The goal is to show what a transparent analysis package can look like.

Compliance boundary: example outputs are for demonstration and method review. Any real manuscript requires researcher review of data provenance, cohort definition, clinical interpretation, ethics/consent status, author contributions, and final claims.

Case overview

Example topicHeart failure survival analysis and Cox regression workflow.
Data typeStructured public example dataset with clinical variables.
Review focusCan a researcher inspect the method choices, numbers, figures, and reproducibility trail?
Outputs shownKaplan-Meier curve, Cox forest plot, method-selection screenshot, number reconciliation screenshot, reference verification screenshot, code reproducibility screenshot.

Output 1: survival curve

Kaplan-Meier survival curve by ejection fraction in the public heart failure demo case
Kaplan-Meier survival curve from the public demo package. The purpose is to demonstrate a reviewable figure output, not to make clinical recommendations.

Output 2: Cox regression forest plot

Multivariable Cox regression forest plot in the public heart failure demo case
Forest plot example for Cox regression output. Any real analysis should be checked for model assumptions, covariates, event counts, and clinical plausibility.

Output 3: method selection notes

Method selection rationale screenshot showing documented statistical method choices
Method-selection notes should explain the data structure, assumptions, alternatives, and final choice so a researcher or statistician can review the workflow.

Output 4: number reconciliation

Number reconciliation screenshot checking consistency across abstract, text, tables, and figures
Number reconciliation helps check whether key sample sizes, hazard ratios, confidence intervals, and p-values are consistent across outputs.

Output 5: reference verification

Reference verification screenshot showing citation checks with DOI or PubMed-style links
Reference verification is designed to make citations traceable. Researchers should still verify final references before submission.

Output 6: reproducibility materials

Code reproducibility screenshot showing analysis script and output trace
When included in scope, reproducibility materials can make it easier to rerun analyses, inspect assumptions, and respond to reviewer questions.

What this case demonstrates

Download the public demo package

The package includes public example data, analysis materials, figures, statistical tables, and reconciliation materials for inspection.

Download demo ZIP How the workflow works