Heart Disorder Detection with Menard Algorithm on Apache Spark
Nowadays, healthcare is facing Big Data processing in order to support medical staff by means of decision making tools. In this context, a challenging topic is the storing and analysis of data in the cardiology field. Electrocardiogram produces signals about the heart health that need to be processed in order to detect a possible disorder. In this paper, we discuss an Apache Spark based tool and that uses the Menard algorithm. In order to validate our solution, we performed experiments on a use case in which the algorithm has been implemented in order to detect heart disorder. Experiments prove the goodness of our approach in terms of performance.
KeywordsBig Data Healthcare Cardiology Heart ECG Arrhythmia
This work has been supported by Cloud for Europe (C4E) Tender: REALIZATION OF A RESEARCH AND DEVELOPMENT PROJECT (PRE-COMMERCIAL PROCUREMENT) ON “CLOUD FOR EUROPE”, Italy-Rome: Research and development services and related consultancy services Contract notice: 2014/S 241-424518. Directive: 2004/18/EC (http://www.cloudforeurope.eu/). Authors would like to thank Fabio Pandolfo for his valuable technical support in this scientific work.
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