Predicting risk of stroke from one's genetic blueprint
(Children’s Hospital Boston) The ability to predict a person’s lifelong risk of stroke would allow clinicians to advise individuals at high risk. In the March issue of Stroke, researchers in the Children’s Hospital Informatics Program report such a statistical model, which draws on 1,313 known genetic predictors. Used in 569 patients presenting with possible stroke, the model, known as a Bayesian network, was able to predict the true occurrence of stroke with 86 percent accuracy.
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