lifelines

Using lifelines to replicate published articles

This project focuces on analysis of survival patients with Aids, with Python library Lifelines

DecenniumClinic is a reproducible Python stack for epidemiology-style cohorts: validation → imputation-in-pipeline random forests → Harrell’s C tuning, plus /health, /ready, and curl-friendly APIs. Built for methods research, not patient care.

C++17 console implementation of Who Wants to Be a Millionaire with validated CSV question banks, a prize ladder and three lifelines

end-to-end survival analysis on 15,054 breast cancer patients using Kaplan–Meier, Cox PH, and Weibull AFT models to identify prognostic factors and evaluate survival outcomes

Applying KaplanMeierFitter model on Time and Events

A repository containing various projects and microprojects.

How long does a track & field world record stand? A survival analysis (Kaplan-Meier + Cox) of ~250 record reigns — and which of today's records is most likely to fall next.

This is a interactive math quiz game in which player has to complete a given math equation that can be of multiplication subtraction or addition in a given time

Project and tutorial for analyzing datasets with Python, pandas, lifelines, matplotlib, statsmodels, and seaborn

Pancreatic Cancer Predictive Pipeline A professional clinical framework for pancreatic cancer prognosis. Combines Kaplan-Meier survival analysis and Cox Regression with an MLOps-powered machine learning pipeline (XGBoost/Random Forest) for real-time, high-recall patient risk stratification.

A biostatistical survival analysis pipeline using Python to evaluate patient prognosis in the Mayo Clinic PBC dataset. Implements Kaplan-Meier estimators and Cox Proportional Hazards models to mathematically process right-censored clinical data and identify mortality risk factors.

Survival analysis of breast cancer clinical data using Kaplan–Meier curves and Cox proportional hazards models in Python

Predicts what happens to passengers after their flight is cancelled, where they go, when they'll actually resolve, and what it costs the airport. Classification vs. a transparent benchmark, survival analysis for timing, and a Passenger Half-Life metric that shows which disrupted groups keep generating pressure for hours.

Survival prediction model on TCGA-BRCA data · Python · Lifelines · Streamlit

Notebooks for "A topic model analysis of TCGA transcriptomic data of breast and lung cancer"

Kaplan-Meier survival analysis and log-rank testing on canine osteosarcoma clinical trail data (ICDC COTC022).