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Automated Assessment Of Disease Progression In Acute Myeloid Leukemia By Probabilistic Analysis Of Flow Cytometry Data, Bartek Rajwa, Paul K. Wallace, Elizabeth A. Griffiths, Murat Dundar
Automated Assessment Of Disease Progression In Acute Myeloid Leukemia By Probabilistic Analysis Of Flow Cytometry Data, Bartek Rajwa, Paul K. Wallace, Elizabeth A. Griffiths, Murat Dundar
Bindley Publications
Objective: Flow cytometry (FC) is a widely acknowledged technology in diagnosis of acute myeloid leukemia (AML) and has been indispensable in determining progression of the disease. Although FC plays a key role as a post-therapy prognosticator and evaluator of therapeutic efficacy, the manual analysis of cytometry data is a barrier to optimization of reproducibility and objectivity. This study investigates the utility of our recently introduced non-parametric Bayesian framework in accurately predicting the direction of change in disease progression in AML patients using FC data. Methods: The highly flexible non-parametric Bayesian model based on the infinite mixture of infinite Gaussian …