Area
Signal Theory and Communications
Signal Theory and Communications
Cristina Soguero-Ruiz received the Telecommunication Engineering degree, the B.Sc. degree in Business Administration and Management, and the M.Sc. degree in Biomedical Engineering from the Rey Juan Carlos University, Madrid, Spain, in 2011 and 2012. She got the PhD in Machine Learning with application in Healthcare and Business Intelligence in 2015. She won the Orange Foundation Best PhD Thesis Award by the Spanish Official College of Telecommunications Engineers. Her main research interests include statistical learning theory, digital signal processing, with application to eHealth, electronic health records, and marketing.
statistical learning theory, digital signal processing, with application to eHealth, electronic health records, and marketing.
Office D201. Departamental III
Universidad Rey Juan carlos
Camino del Molino s/n.
Fuenlabrada, 28943, Madrid, Spain
cristina.soguero@urjc.es
.- Soguero-Ruiz, C., Hindberg, K., Mora-Jiménez, I., Rojo-Álvarez, J. L., Skrøvseth, S. O., Godtliebsen, F., ... & Jenssen, R. (2016). Predicting colorectal surgical complications using heterogeneous clinical data and kernel methods. Journal of biomedical informatics, 61, 87-96.
.- Soguero-Ruiz, C., Hindberg, K., Rojo-Álvarez, J. L., Skrøvseth, S. O., Godtliebsen, F., Mortensen, K., ... & Jenssen, R. (2016). Support vector feature selection for early detection of anastomosis leakage from bag-of-words in electronic health records. IEEE journal of biomedical and health informatics, 20(5), 1404-1415.
.- Soguero-Ruiz, C., Lechuga-Suarez, L., Mora-Jiménez, I., Ramos-Lopez, J., Barquero-Perez, O., Garcia-Alberola, A., & Rojo-Alvarez, J. L. (2013). Ontology for heart rate turbulence domain from the conceptual model of SNOMED-CT. IEEE Transactions on Biomedical Engineering, 60(7), 1825-1833.
.- Soguero-Ruiz, C., Gimeno-Blanes, F. J., Mora-Jiménez, I., Martínez-Ruiz, M. P., & Rojo-Álvarez, J. L. (2012). On the differential benchmarking of promotional efficiency with machine learning modeling (I): Principles and statistical comparison. Expert Systems with Applications, 39(17), 12772-12783.