Examinando por Materia "Reingreso hospitalario"

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    Ítem
    Análisis de explicabilidad en modelos predictivos basados en técnicas de aprendizaje automático sobre el riesgo de re-ingresos hospitalarios
    (Universidad EAFIT, 2023) Lopera Bedoya, Juan Camilo; Aguilar Castro, José Lisandro
    Big Data and medical care are essential to analyze the risk of re-hospitalization of patients with chronic diseases and can even help prevent their deterioration. By leveraging the information, healthcare institutions can deliver accurate preventive care, and thus, reduce hospital admissions. The level of risk calculation will allow planning the spending on in-patient care, in order to ensure that medical spaces and resources are available to those who need it most. This article presents several supervised models to predict when a patient can be hospitalized again, after its discharge. In addition, an explainability analysis will be carried out with the predictive models to extract information associated with the predictions they make, in order to determine, for example, the degree of importance of the predictors/descriptors. In this way, it seeks to make the results obtained more understandable for health personnel.