Modelling chronic kidney disease progression using ABM: a work in progress
Chronic kidney disease (CKD) is a major health problem worldwide. In Spain, the incidence of CKD has increased nearly 17% in ten years, from 2010 to 2020; and in 2020 it had a prevalence of 20% in adults over 60 years. This disease has some characteristics that make it complex; for instance, CKD has...
Guardado en:
| Autores principales: | , , , |
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| Formato: | Objeto de conferencia |
| Lenguaje: | Inglés |
| Publicado: |
2023
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| Materias: | |
| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/155419 |
| Aporte de: |
| Sumario: | Chronic kidney disease (CKD) is a major health problem worldwide. In Spain, the incidence of CKD has increased nearly 17% in ten years, from 2010 to 2020; and in 2020 it had a prevalence of 20% in adults over 60 years. This disease has some characteristics that make it complex; for instance, CKD has a late diagnosis, because the symptoms appear when it is already advanced, and they are not directly related to kidney problems. Furthermore, the causes of the disease are multiple; the most common are arterial hypertension and diabetes. In this context, we believe that simulation and agent-based modelling can provide new tools for assisting professionals in the decision-making process. Therefore, we are proposing the design of a model for CKD progression in order to predict the appearance of renal failure and its evolution in patients through the different states of the disease. Our work is divided into four main stages; and in this article, we present the tasks that have been carried out so far in the first stage which are related to data analysis to define the complexity of the problem. |
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