Deep Convolutional Neural Network Model For Classification Of Atrial Fibrillation

Simple item page
but.event.date23.04.2020cs
but.event.titleStudent EEICT 2020cs
dc.contributor.authorBudíková, Barbora
dc.date.accessioned2021-07-15T11:17:20Z
dc.date.available2021-07-15T11:17:20Z
dc.date.issued2020cs
dc.description.abstractAtrial fibrillation is a very common heart pathology, which is usually detected from electrocardiogram (ECG). This article presents recognition of atrial fibrillation in ECG using deep convolutional neural network. Data used for training the network includes physiological ECG, atrial fibrillation and nine other pathologies. The detection is performed by algorithm in Python language and is being assessed by accuracy and F1 measure.en
dc.formattextcs
dc.format.extent208-211cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationProceedings I of the 26st Conference STUDENT EEICT 2020: General papers. s. 208-211. ISBN 978-80-214-5867-3cs
dc.identifier.isbn978-80-214-5867-3
dc.identifier.urihttp://hdl.handle.net/11012/200560
dc.language.isocscs
dc.publisherVysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.relation.ispartofProceedings I of the 26st Conference STUDENT EEICT 2020: General papersen
dc.relation.urihttps://conf.feec.vutbr.cz/eeict/EEICT2020cs
dc.rights© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.rights.accessopenAccessen
dc.subjectECGen
dc.subjectatrial fibrillationen
dc.subjectconvolutional neural networken
dc.subjectdetectionen
dc.titleDeep Convolutional Neural Network Model For Classification Of Atrial Fibrillationen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.departmentFakulta elektrotechniky a komunikačních technologiícs
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
208-eeict_1.pdf
Size:
716.02 KB
Format:
Adobe Portable Document Format
Description:
Download
Collections
Student EEICT 2020