Real-time brain stroke detection through a learning-by-examples technique- An experimental assessment.

Autor:	Salucci, Marco, Vrba, Jan, Merunka, Ilja, Massa, Andrea
Předmět:	SCATTERING (Physics) SUPPORT vector machines STROKE diagnosis CLASSIFICATION algorithms SUPERVISED learning
Zdroj:	Microwave & Optical Technology Letters; Nov2017, Vol. 59 Issue 11, p2796-2799, 4p
Abstrakt:	The 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. [ABSTRACT FROM AUTHOR]
Databáze:	Complementary Index
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