Publication:
Predicting stroke by combination of sequence pattern Mining and associative classification

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dc.contributor.authorNasingkhun, Sujitra
dc.contributor.authorSongram, Panida
dc.date.accessioned2023-12-16T10:57:13Z
dc.date.available2023-12-16T10:57:13Z
dc.date.issued2028
dc.date.issuedBE2571
dc.description.abstractStroke is a medical emergency that needs immediate medical attention. It is the third cause of death in the world and is the first cause of death of elderly women in Thailand. Stroke needs to be predicted in order to prevent people from the disease and to prepare proper medical treatments for the patients. A number of research works tried to study factors; such as blood pressure; smoking; and cholesterol; for predicting stroke. Unlike the previous works; the association of disease sequence is combined with factors for predicting stroke in this paper. The association is represented in the form of class sequential rules which demonstrate the association of diseases and factors leading to stroke. The combination of sequential pattern mining and associative classification is proposed as a method for generating class sequential rules. The experimental results show that the proposed technique gives high performance for the prediction. In addition; this paper shows top ten association of the disease and factors leading to stroke.
dc.identifier.doi10.23919/INCIT.2018.8584879
dc.identifier.urihttps://harrt.in.th/handle/123456789/8543
dc.language.isoen
dc.publisherIEEE
dc.publisher.placeThailand
dc.subjectโรคหลอดเลือดสมอง
dc.subjectการทำเหมืองข้อมูล
dc.subjectความสัมพันธ์ตามลำดับเวลาของโรค
dc.subjectStroke Detection
dc.subjectDisease Sequence Association
dc.subjectSequential Rule Mining
dc.subjectSequence Classification
dc.subject.isced0322 บรรณารักษ์, สารสนเทศ และการศึกษาจดหมายเหตุ
dc.subject.oecd5.8 นิเทศศาสตร์และสื่อสารมวลชน
dc.titlePredicting stroke by combination of sequence pattern Mining and associative classification
dc.typeเอกสารตีพิมพ์ในการประชุม (Conference Proceedings)
dspace.entity.typePublication
harrt.researchAreaสารสนเทศศาสตร์
harrt.researchGroupบรรณารักษศาสตร์และสารสนเทศศาสตร์
harrt.researchTheme.1Data Science
harrt.researchTheme.2Data Mining
mods.location.urlhttps://ieeexplore.ieee.org/document/8584879
oaire.citation.title2018 International Conference on Information Technology (InCIT)
oairecerif.author.affiliationโรงพยาบาลมหาสารคาม. . นักวิชาการคอมพิวเตอร์
oairecerif.event.name2018 International Conference on Information Technology (InCIT)
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