An associative memory approach to healthcare monitoring and decision making

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Abstract

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. The rapid proliferation of connectivity, availability of ubiquitous computing, miniaturization of sensors and communication technology, have changed healthcare in all its areas, creating the well-known healthcare paradigm of e-Health. In this paper, an embedded system capable of monitoring, learning and classifying biometric signals is presented. The machine learning model is based on associative memories to predict the presence or absence of coronary artery disease in patients. Classification accuracy, sensitivity and specificity results show that the performance of our proposal exceeds the performance achieved by each of the fifty widely known algorithms against which it was compared.
Original languageAmerican English
JournalSensors (Switzerland)
DOIs
StatePublished - 16 Aug 2018

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