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

Abstract : 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.
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Ahmad Al Sayyid, Rafiqul Haque, Yehia Taher, Sara Makki, Ali Jaber. ProgMod: An Analytical Model for Prognosis Prediction of AML Patients Using Survival Regression and Gene Expression Levels. Big Data and Cyber-Security Intelligence, Dec 2018, Beirut, Lebanon. ⟨hal-02353117⟩

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