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| 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: | Artículos |
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