Modeling comorbidity relationships for arterial hypertension patients based on Bayesian networks
| Autor: | Nadezhda Zvartau, Marina Balakhontceva, Vadim V. Elyutin |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
Estimation education.field_of_study Computer science Population Bayesian network medicine.disease Comorbidity 03 medical and health sciences 030104 developmental biology medicine General Earth and Planetary Sciences education General Environmental Science Demography Female population |
| Zdroj: | Procedia Computer Science. 138:238-243 |
| ISSN: | 1877-0509 |
| DOI: | 10.1016/j.procs.2018.10.034 |
| Popis: | In this article Bayesian network that shows relationships between classes and types of chronic diseases were presented. The networks were constructed based on a sample of more than 50,000 outpatients with arterial hypertension. As a result, were observed differences in the comorbidities dynamic of men and women of different ages in the population. In particular, it was found that, over time, the connections between the types of such diseases. In the female population are significantly complicated (as evidenced by the increase in the number of links in the developed model), while for men the opposite picture was observed - with age, the number of connections between comorbidities decreased. This allowed us to conclude that in the considered population, women live longer (by estimation the size of the datasets) and are more inclined to acquire new comorbidities. The male population, in contrast, is subject to early mortality. The connections between comorbidity diseases for men become less complex with time. It means that the healthier the patient is initially, the higher his chances for a long and healthy life in the future. |
| Databáze: | OpenAIRE |
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