Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/25108
Title: Characterization of physiological networks in sleep apnea patients using artificial neural networks for Granger causality computation
Authors: Cárdenas, J.
Orjuela-Cañón, A.
Cerquera, A.
Ravelo García, Antonio G. 
UNESCO Clasification: 3314 Tecnología médica
120304 Inteligencia artificial
Keywords: Artificial neural network
Granger causality
Obstructive sleep apnea syndrome
Brain-heart networks
CPAP
Issue Date: 2017
Journal: Proceedings of SPIE - The International Society for Optical Engineering 
Conference: 13th International Conference on Medical Information Processing and Analysis, SIPAIM 2017 
Abstract: Different studies have used Transfer Entropy (TE) and Granger Causality (GC) computation to quantify interconnection between physiological systems. These methods have disadvantages in parametrization and availability in analytic formulas to evaluate the significance of the results. Other inconvenience is related with the assumptions in the distribution of the models generated from the data.
Description: 13th International Conference on Medical Information Processing and Analysis, SIPAIM 2017; San Andres Island; Colombia; 5-7 October 2017; Code 132645
URI: http://hdl.handle.net/10553/25108
ISBN: 9781510616332
ISSN: 0277-786X
DOI: 10.1117/12.2284957
Source: Proceedings of SPIE - The International Society for Optical Engineering [ISSN 0277-786X] v. 10572, article number 1057219
Rights: by-nc-nd
Appears in Collections:Actas de congresos
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