Presentación de la obra

One of the risks during pregnancy, with high negative impact on both pregnant and fetus, is cardiovascular disease suffering. Early diagnosis and proper treatment of this pathology significantly reduces the risk for pregnant. This problem is characterized by the insufficient availability of experts with knowledge of medical specialties involved, making it difficult to both the diagnosis process and the selection of appropriate treatment. In addition, in the treatment of this problem, there are situations of indetermination, uncertainty, vagueness, and incomplete data, hence the need to create novel computational techniques for supporting clinical decision making. This paper aims at creating a new model based on Neutrosophic Cognitive Maps that integrates diagnosis, treatment, and prediction processes for supporting decision making during the treatment of pregnancies with cardiovascular disease. In order to validate the model, a data base with 1019 cases provided by Cardiovascular and Pregnancy National Service / Gynecology and Obstetrics Hospital Ramón Gonzales Coros, was used. Finally, it is demonstrated in this work the efficient use of the proposed model for treating pregnant with cardiovascular diseases.