dc.contributor.author |
Hruzevskyi, O. A. |
|
dc.contributor.author |
Venger, A. M. |
|
dc.contributor.author |
Minukhin, V. V. |
|
dc.date.accessioned |
2021-08-06T10:04:44Z |
|
dc.date.available |
2021-08-06T10:04:44Z |
|
dc.date.issued |
2020 |
|
dc.identifier.citation |
Hruzevskyi O. A., Venger A. M., Minukhin V. V. Model for predicting the vaginal dysbiosis’ severity according to the index of conditionally pathogenic microflora // Journal of Education, Health and Sport. 2020;10(7):456-464. eISSN 2391-8306. DOI http://dx.doi.org/10.12775/JEHS.2020.10.07.047 |
uk_UA |
dc.identifier.uri |
https://repo.odmu.edu.ua:443/xmlui/handle/123456789/9903 |
|
dc.description.abstract |
A model for predicting the severity of dysbiosis according to the index of
opportunistic pathogenic microflora has been developed. The aim of the study is to identify
the most informative indicators that objectively reflect the condition of the pathological
process and develop a system for predicting the risk of occurrence and severity of dysbiosis
behind these indicators. Statistical processing of data was carried out using variational and
correlation analysis methods using the Application software package Statistica v.10 (StatSoft,
Inc.). At the first stage of the analysis, the index of conditionally pathogenic microflora was
considered as a resultant trait. To identify factors that are more associated with the risk of
developing dysbiosis with IOPM, a selection of significant traits was performed using a
genetic selection algorithm. The prediction of the severity of dysbiosis with IOPM was
considered. The nine factor attributes obtained with the help of mathematical analysis allowed
to predict the severity of vaginal dysbiosis with high accuracy and to calculate the IOPM indices. Phasal nature of development of the immune system reaction during the development
of vaginal dysbiosis is revealed. Possibility of practical use of the developed model is shown. |
uk_UA |
dc.language.iso |
en |
uk_UA |
dc.subject |
index of opportunistic pathogenic microflora |
uk_UA |
dc.subject |
normobiota |
uk_UA |
dc.subject |
prediction model |
uk_UA |
dc.subject |
dysbiosis |
uk_UA |
dc.title |
Model for predicting the vaginal dysbiosis’ severity according to the index of conditionally pathogenic microflora |
uk_UA |
dc.type |
Article |
uk_UA |