Using lifelines to replicate published articles
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Updated
Jan 17, 2022 - Jupyter Notebook
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.
Applying KaplanMeierFitter model on Time and Events
Cox survival validation of 8 DNA-methylation clocks against ~20-year NHANES mortality follow-up (n=2,532)
Project and tutorial for analyzing datasets with Python, pandas, lifelines, matplotlib, statsmodels, and seaborn
Python survival-analysis engine for retention strategy testing: K-Means personas, CoxPH runway modeling, high-risk scenario simulation, Kaplan-Meier curves, and executive PPTX/PDF outputs.
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 prediction model on TCGA-BRCA data · Python · Lifelines · Streamlit
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.
Notebooks for "A topic model analysis of TCGA transcriptomic data of breast and lung cancer"
A repository containing various projects and microprojects.
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
Survival analysis of breast cancer clinical data using Kaplan–Meier curves and Cox proportional hazards models in Python
Analyzed user events from a leading scheduling SaaS platform to uncover what drives activation, engagement, and subscription [Part 2]
It is an interactive Quiz Game built in Java containing a series of M.C.Q based questions with provided lifelines(Expert Opinion, Fifty-fifty, Skip the question, Redeem a lifeline) for user ’s help.
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