ProgMod: An Analytical Model for Prognosis Prediction of AML Patients Using Survival Regression and Gene Expression Levels

An accurate prediction of prognosis to the patient diagnosed with Acute Myeloid Leukemia (AML) is an enormously difficult task. Several solutions have been proposed for prognosis prediction however there is a scope to improve current solutions. In this paper we aim at developing a solution that estimates the survival time that is the Prognosis of patients diagnosed with AML. To that end, we used a machine learning model that is built on an algorithm called Survival Regression. The model consumes as input the Expression Levels of a small number of the genes of the patient.