Automatic classifiers for medical data from doppler unit

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dc.contributor.authorMálek, Jiří
dc.contributor.authorNouza, Jan
dc.contributor.authorKlimovič, Tomáš
dc.date.accessioned2016-05-24
dc.date.available2016-05-24
dc.date.issued2007
dc.description.abstractNowadays, hand-held ultrasonic Doppler units are often used for noninvasive screening of atherosclerosis in arteries of the lower limbs. The mean velocity of blood flow in time and blood pressures are measured on several positions on each lower limb. This project presents soft-ware that is able to analyze such data and classify it in real time into selected diagnostic classes. It is also capable of giving a notice of some errors encountered during meas-uring. At the Department of Functional Diagnostics in the Regional Hospital of Liberec a database of several hun-dreds signals was collected. In cooperation with the spe-cialist, the signals were manually classified into four classes. Consequently selected signal features were ex-tracted and used for training a distance and a Bayesian classifier. Another set of signals was used for evaluating and optimizing the parameters of the classifiers. This paper compares the results of the software with those provided by a human expert. They agreed in 89 % cases.en
dc.formattext
dc.identifier.issn1210-2512
dc.identifier.scopus2-s2.0-84860480756
dc.identifier.urihttps://dspace.tul.cz/handle/15240/16372
dc.identifier.urihttps://www.radioeng.cz/fulltexts/2007/07_02_62_66.pdf
dc.language.isoen
dc.publisherCzech Technical University
dc.publisherTechnická Univerzita v Libercics
dc.publisherTechnical university of Liberec, Czech Republicen
dc.relation.ispartofRadioengineeringen
dc.sourcej-scopus
dc.subjectHand-held ultrasonic Doppler uniten
dc.subjectMedical data recognitionen
dc.subjectPeripheral arterial diseaseen
dc.titleAutomatic classifiers for medical data from doppler uniten
dc.typeArticle
local.accessοpen
local.citation.epage66
local.citation.spage62
local.facultyFaculty of Mechatronics, Informatics and Interdisciplinary Studies
local.fulltextyes
local.identifier.stagRIV/46747885:24220/07:#0001956
local.identifier.wok255863300011
local.relation.issue2
local.relation.volume16
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