Model for predicting the vaginal dysbiosis’ severity according to the index of conditionally pathogenic microflora
<p class="NoSpacing">A model for predicting the severity of dysbiosis according to the index of opportunistic pathogenic microflora has been developed. <em>The aim</em> of the study is to identify the most informative indicators that objectively reflect the condition of t...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Kazimierz Wielki University
2020-07-01
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| Series: | Journal of Education, Health and Sport |
| Subjects: | |
| Online Access: | https://apcz.umk.pl/czasopisma/index.php/JEHS/article/view/33313 |
| _version_ | 1818586533422170112 |
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| author | O. A. Hruzevskyi A. M. Venger V. V. Minukhin |
| author_facet | O. A. Hruzevskyi A. M. Venger V. V. Minukhin |
| author_sort | O. A. Hruzevskyi |
| collection | DOAJ |
| description | <p class="NoSpacing">A model for predicting the severity of dysbiosis according to the index of opportunistic pathogenic microflora has been developed. <em>The aim</em> 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.</p> |
| first_indexed | 2024-12-16T08:54:29Z |
| format | Article |
| id | doaj.art-63208d3557e2482496cb0fbdffeae237 |
| institution | Directory Open Access Journal |
| issn | 2391-8306 |
| language | English |
| last_indexed | 2024-12-16T08:54:29Z |
| publishDate | 2020-07-01 |
| publisher | Kazimierz Wielki University |
| record_format | Article |
| series | Journal of Education, Health and Sport |
| spelling | doaj.art-63208d3557e2482496cb0fbdffeae2372022-12-21T22:37:19ZengKazimierz Wielki UniversityJournal of Education, Health and Sport2391-83062020-07-0110745646410.12775/JEHS.2020.10.07.04726784Model for predicting the vaginal dysbiosis’ severity according to the index of conditionally pathogenic microfloraO. A. Hruzevskyi0A. M. Venger1V. V. Minukhin2Odesa National Medical University Ministry of Health of UkraineOdesa National Medical University Ministry of Health of UkraineI. I. Mechnikoff Institute of Microbiology and Immunology of National Academy of Medical Science of Ukraine<p class="NoSpacing">A model for predicting the severity of dysbiosis according to the index of opportunistic pathogenic microflora has been developed. <em>The aim</em> 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.</p>https://apcz.umk.pl/czasopisma/index.php/JEHS/article/view/33313index of opportunistic pathogenic microfloranormobiotaprediction modeldysbiosis |
| spellingShingle | O. A. Hruzevskyi A. M. Venger V. V. Minukhin Model for predicting the vaginal dysbiosis’ severity according to the index of conditionally pathogenic microflora Journal of Education, Health and Sport index of opportunistic pathogenic microflora normobiota prediction model dysbiosis |
| title | Model for predicting the vaginal dysbiosis’ severity according to the index of conditionally pathogenic microflora |
| title_full | Model for predicting the vaginal dysbiosis’ severity according to the index of conditionally pathogenic microflora |
| title_fullStr | Model for predicting the vaginal dysbiosis’ severity according to the index of conditionally pathogenic microflora |
| title_full_unstemmed | Model for predicting the vaginal dysbiosis’ severity according to the index of conditionally pathogenic microflora |
| title_short | Model for predicting the vaginal dysbiosis’ severity according to the index of conditionally pathogenic microflora |
| title_sort | model for predicting the vaginal dysbiosis severity according to the index of conditionally pathogenic microflora |
| topic | index of opportunistic pathogenic microflora normobiota prediction model dysbiosis |
| url | https://apcz.umk.pl/czasopisma/index.php/JEHS/article/view/33313 |
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