نبذة مختصرة : One of the risks during pregnancy, with high negative impact on both pregnant and fetus is cardiovascular disease suffering. Early diagnosis and appropriate treatment of this pathology significantly reduce the risk for pregnant. The treatment of pregnant women with heart diseases is characterized by the insufficient availability of experts with knowledge of medical specialties involved, and by the presence of situations of indeterminacy, uncertainty, vagueness, and incomplete data. Hence the need to create novel computational techniques for supporting clinical decision making during the treatment of these diseases. In this paper, we suggest a new model based on Neutrosophic Cognitive Map that integrates diagnosis, treatment, and prognosis processes for supporting clinical decision making during the treatment of pregnant women with cardiovascular diseases. The model introduces a new approach to represent the map’s connections, by using Triangular Neutrosophic Numbers, making it possible to quantify the truth, indeterminacy, and falsity degrees of experts’ preferences. The new model aims to improve the accuracy of diagnosis and treatment of heart diseases during pregnancy; and to mitigate the lack of expertise in this area. In validation process, a data base with 1019 cases provided by Cardiovascular and Pregnancy National Service / Gynecology and Obstetrics Hospital Ramón Gonzales Coros is used, and model’s results are evaluated by experts to demonstrate the efficiency of the proposed model for treating these diseases during pregnancy. ; Uno de los riesgos durante el embarazo, con mayor impacto negativo tanto para la gestante como para el feto, es el padecimiento de las enfermedades cardiovasculares. El diagnóstico temprano y el adecuado tratamiento de esta patología disminuye significativamente el riesgo para las pacientes. El tratamiento de las embarazadas cardiópatas se caracteriza por la insuficiente disponibilidad de expertos que dominen las especialidades médicas involucradas, y la presencia de situaciones ...
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