dc.contributor.author | Karaolis, Minas A. | en |
dc.contributor.author | Moutiris, Joseph Antoniou | en |
dc.contributor.author | Papaconstantinou, L. | en |
dc.contributor.author | Pattichis, Constantinos S. | en |
dc.creator | Karaolis, Minas A. | en |
dc.creator | Moutiris, Joseph Antoniou | en |
dc.creator | Papaconstantinou, L. | en |
dc.creator | Pattichis, Constantinos S. | en |
dc.date.accessioned | 2019-11-13T10:40:38Z | |
dc.date.available | 2019-11-13T10:40:38Z | |
dc.date.issued | 2009 | |
dc.identifier.isbn | 978-1-4244-3296-7 | |
dc.identifier.uri | http://gnosis.library.ucy.ac.cy/handle/7/54219 | |
dc.description.abstract | Although significant progress has been made in the diagnosis and treatment of coronary heart disease (CHD), further investigation is still needed. The objective of this study was to develop a data mining system using association analysis based on the apriori algorithm for the assessment of heart event related risk factors. The events investigated were: myocardial infarction (MI), percutaneous coronary intervention (PCI), and coronary artery bypass graft surgery (CABG). A total of 369 cases were collected from the Paphos CHD Survey, most of them with more than one event. The most important risk factors, as extracted from the association rule analysis were: sex (male), smoking, high density lipoprotein, glucose, family history, and history of hypertension. Most of these risk factors were also extracted by our group in a previous study using the C4.5 decision tree algorithms, and by other investigators. Further investigation with larger data sets is still needed to verify these findings. ©2009 IEEE. | en |
dc.source | Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009 | en |
dc.source | 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009 | en |
dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-77950974607&doi=10.1109%2fIEMBS.2009.5334656&partnerID=40&md5=582e57d7ea2d771947263909fd27e87d | |
dc.subject | Diagnosis | en |
dc.subject | Heart | en |
dc.subject | Risk factors | en |
dc.subject | Biology | en |
dc.subject | Myocardial infarction | en |
dc.subject | Data sets | en |
dc.subject | Data mining | en |
dc.subject | Glucose | en |
dc.subject | Decision trees | en |
dc.subject | C4.5 decision tree algorithm | en |
dc.subject | Coronary artery bypass graft | en |
dc.subject | Coronary heart disease | en |
dc.subject | Percutaneous coronary intervention | en |
dc.subject | Related risk | en |
dc.subject | Apriori algorithms | en |
dc.subject | Association analysis | en |
dc.subject | Association rules | en |
dc.subject | Associative processing | en |
dc.subject | Data mining system | en |
dc.subject | High density lipoprotein | en |
dc.title | Association rule analysis for the assessment of the risk of coronary heart events | en |
dc.type | info:eu-repo/semantics/conferenceObject | |
dc.identifier.doi | 10.1109/IEMBS.2009.5334656 | |
dc.description.startingpage | 6238 | |
dc.description.endingpage | 6241 | |
dc.author.faculty | 002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences | |
dc.author.department | Τμήμα Πληροφορικής / Department of Computer Science | |
dc.type.uhtype | Conference Object | en |
dc.description.notes | <p>Conference code: 79618 | en |
dc.description.notes | Cited By :17</p> | en |
dc.contributor.orcid | Pattichis, Constantinos S. [0000-0003-1271-8151] | |
dc.gnosis.orcid | 0000-0003-1271-8151 | |