R package for Kaplan-Meier Plot: Modified ggkm

Utilising a publicly-available and small dataset of ~5K patients from Kaggle, to practice health data analysis.

Resources for Survival Analysis

Graphical Presentation of Clinical Data in Oncology Studies Using R

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.

Survival Analysis of cancer patient data

HeartPredict is a Python library designed to analyze and predict heart failure outcomes using patient data.

This project aims to analyze customer churn data to identify key drivers and suggest actionable strategies to improve retention.

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

Survival Analysis for Glioblastoma Multiforme

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

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.

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

Survival Analysis of Lung Cancer Patients

survival curves in ggplot2

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

Generating Kaplan Meier plots using gene expression data