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Predicting healthcare cost of diabetes using machine learning models
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Autores
González Rodríguez, Javier Leonardo
Díaz Carnicereo, Javier
Vivas Consuelo, David
González de Julian, Silvia
Pinzón Espitia, Olga Lucia
Fecha
2019-07
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Universitat Politécnica de Valncia
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Abstract
Diabetes mellitus (DM) describes a group of metabolic disorders characterised by high blood glucose levels. People with diabetes have an increased risk of developing several serious lifethreatening health problems resulting in higher medical care costs, reduced quality of life and increased mortality [1] DM, like the majority of non-contagious chronic diseases, is associated with multimorbidity, defined in the growing literature as the existence of two or more chronic conditions [2,3]. Multimorbidity causes a negative impact on both clinical and health indicators and primary health care costs [1,4]. While true that the analysis of multimorbidity in this type of population is relatively new, the tendency towards this approach to the study of chronic diseases is ever increasing.
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Keywords
Diabetes mellitus Type II , Infarction , Stroke , Retinopathy , Renal failure
