Survival Analysis of Lung Cancer Patients

A Python distribution of iCARE, a tool for individualized Coherent Absolute Risk Estimation.

Breast Cancer Survival Analysis using SAS on METABRIC dataset to identify key survival factors with Kaplan-Meier, Cox models, and gamma distributions

KM plots and Cox Proportional Hazards model for feature selection

CoxKAN: Extending Cox Proportional Hazards Model with Symbolic Non-Linear Log-Risk Functions for Survival Analysis

survival analysis on cirrhosis data from mayo clinic study: kaplan-meier estimator/curve, log rank test, cox proportional hazards model

Methodology research comparing statistical and ML methods of competing risks analysis

Exploring disparities in the COMPAS algorithm: an analysis of recidivism predictions among demographic groups.

A comprehensive end-to-end survival analysis project using classical and deep learning models with clinical data, including preprocessing, modeling, evaluation, and interpretability.

Federated algorithm for coxph in Vantage6 v4

Estimating survival predictions

Python implementation of extracting body weight dynamics in diversity outbred mice using ARHMM.

This repository contains Python code for performing Cox proportional hazards model analysis tailored to crossover study designs.

WhenDidThatHappen is an R package for preparing survival analyses. It takes your Datetimes and derives time-to-event variables for use in Kaplan-Meier models, Cox Proportional Hazards models, Competing Risks models, etc. It supports right-censored simple and composite outcomes, with optional blanking periods and minimum observation periods.

Coursework, Stata code, and notes for PBHS 32700: Biostatistical Methods (Spring 2024, University of Chicago). Topics include contingency tables, logistic regression, Poisson and negative binomial models, and survival analysis using Kaplan-Meier, Cox, and parametric models. The course emphasizes categorical and time-to-event analysis using Stata.

A JavaScript wrapper for the WebAssembly module of iCARE Python (pyicare) package.

Biostatistics internship on proteomics and cancer avoidance