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Analysis Of Relapse In Leukemia Patients With Missing Data Using An Extension Of The Em Algorithm, Braydon Schaible
Analysis Of Relapse In Leukemia Patients With Missing Data Using An Extension Of The Em Algorithm, Braydon Schaible
GS4 Georgia Southern Student Scholars Symposium
Introduction: Acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL) are two types of acute leukemia. When complete remission of leukemia has not been achieved or the disease refracts to its stage in initial chemotherapy, relapse occurs. Leukemia has poor prognosis for patients with relapse. This sample included AML and ALL patients. The purpose of this study was to use and extension of the Expectation-Maximization (EM) algorithm in order to find significant factors that affect the occurrence of relapse in leukemia patients with missing data.
Methods: The EM logistic model consists of three steps. First, the initial logistic regression intercept …