bayesian classifier for medical data from doppler unit

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ID: 165927
2006
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Abstract
Nowadays, hand-held ultrasonic Doppler units (probes) are often used for noninvasive screening of atherosclerosis in the 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. By listening to the acoustic signal generated by the device or by reading the signal displayed on screen, a specialist can detect peripheral arterial disease (PAD).This project aims to design software that will be able to analyze data from such a device and classify it into several diagnostic classes. At the Department of Functional Diagnostics at the Regional Hospital in Liberec a database of several hundreds signals was collected. In cooperation with the specialist, the signals were manually classified into four classes. For each class, selected signal features were extracted and then used for training a Bayesian classifier. Another set of signals was used for evaluating and optimizing the parameters of the classifier. Slightly above 84 % of successfully recognized diagnostic states, was recently achieved on the test data. 
Reference Key
mlek2006actabayesian Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;J. Málek
Journal the journal of nutrition
Year 2006
DOI
DOI not found
URL
https://ojs.cvut.cz/ojs/index.php/ap/article/view/846
Keywords
civil engineering (general)

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