M.Sc. Thesis: Survival Analysis on Orthopedic Disease Data

Context: Primary field data collection on real orthopedic disease patients.

Objective: Identify the optimal predictive model for disease recurrence.

Methodology: Applied Kaplan-Meier curves, Log-Rank tests, hazard modeling, and Random Survival Forests across two successive research projects.

Models Evaluated: Cox PH, XGBoost, CoxBoost, GLMBoost, GLM, CForest.

Outcome: Comparative evaluation of 6 survival models to determine the best predictor for disease recurrence, with findings documented in a full research thesis.