Abstract
AbstractThe real‐time detection of brain strokes is addressed within the Learning‐by‐Examples (LBE) framework. Starting from scattering measurements at microwave regime, a support vector machine (SVM) is exploited to build a robust decision function able to infer in real‐time whether a stroke is present or not in the patient head. The proposed approach is validated in a laboratory‐controlled environment by considering experimental measurements for both training and testing SVM phases. The obtained results prove that a very high detection accuracy can be yielded even though using a limited amount of training data.
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