CUDA Implementation of Heart Health Risk Assessment System Using Ontologies
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2015, Vol 3, Issue 4
Abstract
Heart attack is one of the leading causes of death in both developed and developing countries. The abnormal physical activity of the person which leads to heart attack determined using data mining techniques over data gathered from their smartphone`s sensors like accelerometers, gyroscope, magnetic sensors. One of the primary challenges is to detect lack of real time response to the risk because Physical activity monitoring datasets are quite large and involves heavy computations for classification. These tasks are often complex and computationally expensive which result in a demand for high performance computing platforms. Random Forests (RF) has been proven to be a competitive algorithm regarding both computation time and classification performance and it is a suitable candidate for parallelization; implement random forest algorithm using CUDA (Compute Unified Device Architecture) can increase the performance of classification. We present an alert management tool that supports cares in their task of validating alarms raised by the system using ontology techniques.
Authors and Affiliations
G. Rajesh, R. Thiruvenkadam
Keywords
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