Decoding Hospitalisation Predictors

A Data-Driven Analysis Using Logistic Regression in Multiple Myeloma Patients

This project presents an analysis of hospitalisation risks among multiple myeloma patients using clinical data from a hospital. A logistic regression model is developed and refined to identify key hospitalisation predictors. The research explored various factors contributing to the hospitalisation of multiple myeloma patients, offering insights into risk factors and enhancing predictive modelling techniques in healthcare. The findings provide insights into hospitalisation risk factors and predictive modelling in healthcare settings. Keywords: Multiple Myeloma, Hospitalisation Risk, Logistic Regression, Predictive Modelling, Disease Modelling