Abstract

OCHOA REYES, Alexeis Joel; ORELLANA GARCIA, Arturo; SANCHEZ CORALES, Yovannys  and  DAVILA HERNANDEZ, Frank. Web component for the analysis of clinical information using the technique of clustering data mining. RCIM [online]. 2014, vol.6, n.1, pp. 5-16. ISSN 1684-1859.

The digitization of the different processes and automation services generate large volumes of information. Data mining (DM) is an artificial intelligence technique that allows finding non-trivial information residing in stored data. This research aims to develop a view of analysis for the Integral System for Primary Health Care (SIAPS), using grouping technique framed on Simple K-Means algorithm, with the goal of completing an analysis of the patients' clinical information, for it raises the extraction of knowledge from data warehouse powered by the repository of electronic medical records. The research is based on the free distribution tool WEKA, it works in isolation of SIAPS, the interface, as well as the views, models and reports generated by WEKA are sometimes difficult to understand by health professionals, who do not necessarily have to possess advanced knowledge of new information technologies. For the development of the solution was used Java 1.6 as a programming language, JBoss 4.2 as the application Server and Eclipse 3.4 as a development platform. PostgreSQL 8.4 was used as Database Management System and the integration framework SEAM. Java Enterprise Edition 5.0 platform was used during the whole process. An analysis view to facilitate the understanding of the generated models is expected as a result, to support the process of making clinical decisions.

Keywords : warehouse; knowledge extraction; artificial intelligence; data mining; Simple K-Means; analysis view.

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