Conditional Probability For Identification of High Risk Event of Stroke

Abstract

The beginning of stroke might be identified with a high confident, in particular in those cases where patients have an old diagnosis of type-II diabetes. More than an identification, the behavior of patient can be seen as a type of sequence to central event of stroke. In this paper, the variables that would lead to central event, are seen as conditions that enhance the central event. Therefore, it is postulated the idea that stroke is a probabilistic event caused by conditional probabilities. Because this argument, the full risk probability is estimated and a simulation is carry out. In this manner, stroke can be seen as a probability that is maximized by a weight function. Early recognition of this would be critic to clinicians in order to apply the best pharmacological strategy along the first minutes of stroke.