ProgMod: An Analytical Model for Prognosis Prediction of AML Patients Using Survival Regression and Gene Expression Levels - Archive ouverte HAL Access content directly
Conference Papers Year : 2018

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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Dates and versions

hal-02353117 , version 1 (07-11-2019)

Identifiers

  • HAL Id : hal-02353117 , version 1

Cite

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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