%0 Conference Proceedings
%T Heart Disorder Detection with Menard Algorithm on Apache Spark
%+ University of Messina
%+ Centro Neurolesi Bonino Pulejo Messina (IRCCS Messina)
%A Carnevale, Lorenzo
%A Celesti, Antonio
%A Fazio, Maria
%A Bramanti, Placido
%A Villari, Massimo
%Z Part 7: Industrial Applications of Service and Cloud Computing
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 6th European Conference on Service-Oriented and Cloud Computing (ESOCC)
%C Oslo, Norway
%Y Flavio De Paoli
%Y Stefan Schulte
%Y Einar Broch Johnsen
%I Springer International Publishing
%3 Service-Oriented and Cloud Computing
%V LNCS-10465
%P 229-237
%8 2017-09-27
%D 2017
%R 10.1007/978-3-319-67262-5_17
%K Big Data
%K Healthcare
%K Cardiology
%K Heart
%K ECG
%K Arrhythmia
%Z Computer Science [cs]Conference papers
%X 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.
%G English
%Z TC 2
%Z WG 2.14
%2 https://inria.hal.science/hal-01677608/document
%2 https://inria.hal.science/hal-01677608/file/449571_1_En_17_Chapter.pdf
%L hal-01677608
%U https://inria.hal.science/hal-01677608
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-WG
%~ IFIP-ESOCC
%~ IFIP-TC2
%~ IFIP-WG2-14
%~ IFIP-LNCS-10465