Self-Management to Anticipate Stroke in Diabetic Patients Through Algorithm Based on Probability of Bayes

This paper presents a scheme of self-management that employs directly the theorem of Bayes to calculate realistic probabilities to experience stroke in the shortest and middle terms. In concrete the probabilities might be used in an application by which diabetic patients can carry out by themselves periodical measurements of probabilities of risk. It is emphazised the fact that Bayes rule can be powerful but used as tool to predict stroke might also to trigger false alarms or be blind to stroke.