Optimización de los Diagnósticos Médicos Mediante Técnicas de Minería de Datos (Journal on studies and research of academic knowledge, 2016)
The objective of this paper was to define patterns of patients under similar conditions, for the optimization of medical diagnostics using data mining techniques, specifically classification techniques applied to Latin American Center of Perinatology database, which have the history of pregnant attending prenatal checkups in the Encarnación Regional Hospital, between 2009 and 2014. During the implementation of the project, it was carried out the analyses of possible causes of high blood pressure; premature birth and premature membrane rupture in pregnant. Classifiers indicated a high percentage of accuracy in the results, for example, a classifier indicated 95% accuracy determining the main cause of high blood pressure induced by pregnancy the hypertension historic of the patient. Considering the high percentage of accuracy of the classifiers, the conclusion is that the patterns defined by the classification algorithms are valid for the medical diagnosis of prenatal care, and through these patterns, some medical theories are confirmed, such as the importance of prenatal consultations, the incidence of personal or family history, and others.
Keywords: Data Mining; Classification; Patterns; Medical Diagnosis; Pregnancy