Aplicación de redes complejas al estudio de datos de gestión sanitaria: una perspectiva desde la minería de datos
ABSTRACT: Healthcare management is one of the first-class issues in any modern society. At the same time, new data mining techniques and tools are hatching as a response to an ever growing number of so-called big data applications; in particular, complex networks and network science are consolidatin...
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| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2014 |
| País: | España |
| Institución: | Universidad de Cantabria (UC) |
| Repositorio: | UCrea Repositorio Abierto de la Universidad de Cantabria |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.unican.es:10902/5946 |
| Acceso en línea: | http://hdl.handle.net/10902/5946 |
| Access Level: | acceso abierto |
| Palabra clave: | Healthcare Big data Complex networks Bayesian networks Sanidad Redes complejas Redes bayesianas |
| Sumario: | ABSTRACT: Healthcare management is one of the first-class issues in any modern society. At the same time, new data mining techniques and tools are hatching as a response to an ever growing number of so-called big data applications; in particular, complex networks and network science are consolidating as the tool of choice for the analysis of many non-relational unstructured data sources. In this work we put in contact these two worlds by analysing the characteristics of a diagnoses network emerged from national public healthcare system data. Different methodologies to extract and transform the data are explored, and several results evidencing interesting patterns in the data are presented. Additionally, a complementary analysis from the point of view of Bayesian networks is as well proposed, establishing a comparative between both approaches |
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