SU-E-T-51: Bayesian Network Models for Radiotherapy Error Detection.

Abstract

PURPOSE To develop a probabilistic model of radiotherapy plans using Bayesian networks that will detect potential errors in radiation delivery. METHODS Semi-structured interviews with medical physicists and other domain experts were employed to generate a set of layered nodes and arcs forming a Bayesian Network (BN) which encapsulates relevant… (More)
DOI: 10.1118/1.4888381

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Cite this paper

@article{Kalet2014SUET51BN, title={SU-E-T-51: Bayesian Network Models for Radiotherapy Error Detection.}, author={Alan M. Kalet and Mark H. Phillips and John H. Gennari}, journal={Medical physics}, year={2014}, volume={41 6}, pages={233} }