Automated classification system (ACS) for detection of high risk groups exposed to radiation

The paper presents the results of using an experimental version of the automatic classifying system (ACS) based on unstatistical methods of recognizing the images with estimate calculation algorithms. According to 21 blood parameters obtained on an automatic analyser, ACS could divide, at higher tha...

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Bibliographic Details
Published inMeditsinskaia tekhnika no. 6; p. 9
Main Authors Stavitskiĭ, R V, Guslistyĭ, V P, Zubrikhina, G P
Format Journal Article
LanguageRussian
Published Russia (Federation) 01.11.1994
Subjects
Algorithms
Automation - methods
Blood - radiation effects
Case-Control Studies
Environmental Exposure
Humans
Radiation Dosage
Radioactive Fallout - adverse effects
Radioactive Hazard Release
Risk Assessment
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Summary:The paper presents the results of using an experimental version of the automatic classifying system (ACS) based on unstatistical methods of recognizing the images with estimate calculation algorithms. According to 21 blood parameters obtained on an automatic analyser, ACS could divide, at higher than 90% significance, groups of persons living in the polluted areas of the towns of Klintsy and Zlynka who have accumulated mean radiation dose of 15 and 63 mZv, respectively. The results suggest that ACS may be used to divide subjects into risk groups in terms of exposures to unfavorable environmental factors.
ISSN:0025-8075