Technical Project

Clinical Trial Survival Analysis

Kaplan-Meier survival curve estimation for medical research data.

Interactive Visualization

Live Python Simulation Data

Kaplan-Meier Survival Estimates

015304560Time (Months)00.250.50.751Survival Probability
  • Control Group
  • Treatment Group

Step function shows the probability of survival over time. Treatment group shows significantly better outcomes (p < 0.001).

The Concept (In Plain English)

In medical trials, we need to know not just *if* a treatment works, but *how long* it keeps patients healthy. But patients drop out of studies at different times, making simple averages misleading. This project uses 'Survival Analysis' to account for those dropouts. It draws a curve showing the probability of survival over time, allowing researchers to fairly compare a new drug against a placebo even with messy, incomplete data.

The Build (Technical Deep Dive)

This project implements the Kaplan-Meier estimator to generate survival curves from right-censored clinical trial data. It handles 'censored' subjects (those who leave the study or survive past the end) to provide an unbiased estimate of the survival function. The interactive visualization plots survival probability against time, complete with confidence intervals and censorship markers, mimicking professional biostatistical reporting tools.

Key Metrics

MethodKaplan-Meier
Data TypeRight-Censored
Confidence95% CI

Tech Stack

BiostatisticsRSurvival AnalysisData Viz