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Kaplan-Meier plot maker

Upload survival data and get a Kaplan-Meier curve with group comparisons, a log-rank p-value, censoring marks, and a numbers-at-risk table — publication-ready, no R or Python.

Why use it

Survival analysis built in

Group comparison, log-rank test, confidence bands, censoring ticks, and a risk table — the things reviewers expect — without writing survival/lifelines code.

No coding

Describe the plot in plain language; MindPlot runs the analysis and renders the figure.

Journal-ready output

Clean styling and editable SVG / high-DPI PDF export for submission.

How it works

1

Upload survival data

Provide a table with time-to-event, an event/censoring indicator, and an optional grouping column.

2

Add groups & stats

Compare arms, add the log-rank p-value, confidence intervals, and a numbers-at-risk table.

3

Export the figure

Download a publication-ready SVG/PDF, or refine colours and labels first.

What you can do with it

Clinical outcomes

Compare survival between treatment and control arms.

Oncology research

Show progression-free or overall survival across subgroups.

Reliability / time-to-failure

Any time-to-event analysis maps onto a Kaplan-Meier curve.

Frequently asked questions

What columns do I need?

A time-to-event column, an event indicator (1 = event, 0 = censored), and optionally a group column to compare arms.

Can it compute the log-rank p-value?

Yes — add a log-rank test for group comparisons, plus confidence bands and a numbers-at-risk table.

Do I need R or the survival package?

No — the Kaplan-Meier plot maker is no-code; you upload data and describe the figure in plain language.

Is the output publication-ready?

Yes — journal-grade styling with editable SVG and high-DPI PDF/PNG/EPS export.

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