Advances in Artificial Intelligence - IBERAMIA 2016

Abstract

Severe Maternal Morbidity is a public health issue. It may occur during pregnancy, delivery, or puerperium due to conditions (hypertensive disorders, hemorrhages, infections and others) that put in risk the women’s or baby’s life. These conditions are really difficult to detect at an early stage. In response to the above, this work proposes using several machine learning techniques, which are considered most relevant in a bio-medical setting, in order to predict the risk level for Severe Maternal Morbidity in patients during pregnancy. The population studied correspond to pregnant women receiving prenatal care and final attention at E.S.E Cl´ınica de Maternidad Rafael Calvo in Cartagena, Colombia. This paper presents the preliminary results of an ongoing project, as well as methods and materials considered for the construc- tion of the learning models.