Bioinformatics Commons^™

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 …