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Classification of oximetry signals using Bayesian neural networks to assist in the detection of obstructive sleep apnoea syndrome

<24> This paper provides a statistically rigorous analysis of the improvements in classification performance achieved with Bayesian machine-learning models rather than maximum likelihood or the conventional clinical indices for a complex medical diagnostic task. It was the result of an international collaboration with the University of Valladolid, Spain.