Perform a survival analysis based on the time-to-event (death event) for the subjects. Compare machine learning models to assess the likelihood of a death by heart failure condition. This can be used to help hospitals in assessing the severity of patients with cardiovascular diseases and heart failure condition.

Resources for Survival Analysis

R package for Kaplan-Meier Plot: Modified ggkm

Kaplan-Meier-Estimator also known as the product limit estimator.

Survival Analysis of Lung Cancer Patients

🍊 ➕ Survival Analysis add-on for Orange3 data mining suite.

Survival Analysis

survival curves in ggplot2

Use of clinical EHR data and codelists to investigate all-cause mortality between proton pump inhibitor (PPI) and histamine H2-receptor antagonist (H2RA) exposure groups.

Generating Kaplan Meier plots using gene expression data

I proved the probabilities of freedom from biochemical recurrence (BCR) among prostate cancer patients are significantly different using stratified Logrank test. I also built a Cox's PH model to identify which genes and demographic factors have effect on survival.

Survival Analysis for Glioblastoma Multiforme

Survival analysis in R for Public Health (Imperial College London through Coursera)