Estimation of demand for medical like strategy of administration care in cardiology in Bogotá, through neural networks
Keywords:
Artificial Intelligence, Artificial Neural Network, Training, Trend, Cardiovascular, Myocardium, Vascular System, Risk Factors, Early Detection, prevention.Abstract
Recent studies published in scientific journals indicate that the number of people diagnosed with Cardiovascular Diseases (CVD) worldwide is increasing and our country is no exception, with myocardial infarction and stroke being the two main causes of death related and the fastest growing in the so-called Noncommunicable Diseases (NCDs). This makes us see the need to reliably estimate the growth of the demand for care in CVD pathologies, so that these results are used by the expense managers to program the investment in infrastructure and resources tailored to this demand. Likewise, to take the necessary measures to generate strategies for early prevention and change of habits, based on the risk factors that most affect the generation of CVD. The data associated with CVD for this study were taken from open information provided by the National Administrative Department of Statistics DANE and the Bogota Health Observatory of the District Health Secretariat of Bogotá. Once these data were parameterized and normalized, they were used to train and validate an RNA created for this estimate, this allowed us to glimpse the growth of this demand and therefore the need to take action on the matter before the Colombian health system collapses.
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