A preeclampsia diagnosis approach using Bayesian networks

Conference Paper
Moreira, Mário W. L. . 2016
Bayesian networks; Decision support systems; Hypertencion; Modeling; Pregnancy
Conference Name: 
2016 IEEE International Conference on Communications, ICC 2016
Conference Location: 
Kuala Lumpur; Malaysia
Conference Date: 
Sunday, May 22, 2016
Sponsoring Organization: 
Publication Abstract: 

Hypertension is the main cause of maternal death. Preeclampsia can affect pregnant women before or during pregnancy. Identification of patients with higher risk for preeclampsia allows some precautions that are taken to prevent its severe disease and subsequent complications. In medicine, there are different situations that deal with a large range of information, which needs a thorough assessment to be able to help experts in the decision-making process. Smart decision support systems allow grouping all existing information and finding pertinent information from it. Bayesian networks offer models that allow the information capture and handle situations of uncertainty. This paper proposes the construction of a system to support intelligent decision applied to the diagnosis of preeclampsia using Bayesian networks to help experts in the pregnant's care. The processes of qualitative and quantitative modeling to the construction of a network are also presented. The main contribution of this work includes the presentation of a Bayesian network built to help decision makers in moments of uncertainty in care of pregnant women. © 2016 IEEE.