Resumen

CHOQUE FORRA, Daniela Patricia  y  MAMANI MAMANI, Jessyca Liset. Prediction of Survival in Heart Failure. Rev. Inv. Est. I. [online]. 2020, vol.12, n.1, pp. 77-101. ISSN 2415-2323.

Abstract Justificaron: Given that currently diseases are already common among us, one that has a wide range is Heart Failure, which can arise for various reasons and these apply to how deadly it can be. The objective is to predict survival in heart failure, counting on a dataset that contains clinical records of patients with heart failure. Different Machine Learning algorithms were used from which the best model was selected and then used in a graphical interface. Data analysis was also carried out to observe the influence they have regarding Heart Failure. The methodology used was quantitative with an exploratory design. An analysis of each factor in heart failure was presented, taking points such as gender, or some other type of disease.

Palabras llave : Heart; failure; prediction.