Bayesian Recognition Procedures with Independent Signs of Inflammatory Processes in Gliomas, Metastases and Meningiomas by Indicators of Erythrocyte Sedimentation Rate
Introduction. The article discusses the application of Bayesian recognition procedures with independent signs in relation to the data of the modified erythrocyte sedimentation rate, which were taken from patients with gliomas, metastases, meningiomas, craniocerebral concussion and from a group of he...
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V.M. Glushkov Institute of Cybernetics
2021
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oai:doaj.org-article:799b047f1b9f4a2ca9a4d2bf80fa01ef2021-11-08T19:44:54ZBayesian Recognition Procedures with Independent Signs of Inflammatory Processes in Gliomas, Metastases and Meningiomas by Indicators of Erythrocyte Sedimentation Rate2707-45012707-451X10.34229/2707-451X.21.3.3https://doaj.org/article/799b047f1b9f4a2ca9a4d2bf80fa01ef2021-09-01T00:00:00Zhttp://cctech.org.ua/13-vertikalnoe-menyu-en/272-abstract-21-3-3-artehttps://doaj.org/toc/2707-4501https://doaj.org/toc/2707-451XIntroduction. The article discusses the application of Bayesian recognition procedures with independent signs in relation to the data of the modified erythrocyte sedimentation rate, which were taken from patients with gliomas, metastases, meningiomas, craniocerebral concussion and from a group of healthy people. Purpose of the article. Improving the efficiency of recognition of inflammatory processes in gliomas, metastases and meningiomas by indicators of erythrocyte sedimentation rate using optimal recognition procedures with independent signs. Results. In previous articles by the authors, an attempt was made to recognize inflammatory processes by indicators of the modified erythrocyte sedimentation rate caused by brain cancer using Bayesian recognition procedures based on a single substance. In this work, a new model was built using several independent signs (different substances) at once. The results obtained on the basis of the new model significantly increased their efficiency in relation to the models that were used earlier. Such an increase in all comparisons ranged from 3 to 12 %, and up to almost 94 %. If earlier it was possible to recognize only combinations of diagnoses in which there were no more than two diagnoses, then in this work for the first time it was possible to recognize three diagnoses at once. At the same time, the recognition efficiency became slightly more than 70 %. An attempt was also made to recognize more than three diagnoses, but the new model did not give significant results, slightly exceeding 50 % when recognizing four diagnoses at once. Conclusions. Thanks to the use of Bayesian recognition procedures with independent signs, it was possible to significantly increase the recognition of inflammatory processes caused by brain cancer. The modified erythrocyte sedimentation rate, which is an auxiliary tool in the diagnosis of gliomas, allows one or another pathology to be determined in the preoperative period, since the pathology is finally determined only when studying a surgically removed tumor. In the postoperative period, such a modification is an indicator of repeated recurrence of gliomas. It was also possible to significantly increase the recognition of inflammatory processes caused by non-oncological disease (traumatic brain injury) in relation to oncological processes in gliomas, metastases and meningiomas.Andrii TarasovV.M. Glushkov Institute of Cyberneticsarticlebayesian recognition procedureindependent signsgliomasmetastasesmeningiomasmodified erythrocyte sedimentation ratecomplex parameterCyberneticsQ300-390ENRUUKКібернетика та комп'ютерні технології, Iss 3, Pp 34-42 (2021) |
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bayesian recognition procedure independent signs gliomas metastases meningiomas modified erythrocyte sedimentation rate complex parameter Cybernetics Q300-390 |
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bayesian recognition procedure independent signs gliomas metastases meningiomas modified erythrocyte sedimentation rate complex parameter Cybernetics Q300-390 Andrii Tarasov Bayesian Recognition Procedures with Independent Signs of Inflammatory Processes in Gliomas, Metastases and Meningiomas by Indicators of Erythrocyte Sedimentation Rate |
| description |
Introduction. The article discusses the application of Bayesian recognition procedures with independent signs in relation to the data of the modified erythrocyte sedimentation rate, which were taken from patients with gliomas, metastases, meningiomas, craniocerebral concussion and from a group of healthy people.
Purpose of the article. Improving the efficiency of recognition of inflammatory processes in gliomas, metastases and meningiomas by indicators of erythrocyte sedimentation rate using optimal recognition procedures with independent signs.
Results. In previous articles by the authors, an attempt was made to recognize inflammatory processes by indicators of the modified erythrocyte sedimentation rate caused by brain cancer using Bayesian recognition procedures based on a single substance. In this work, a new model was built using several independent signs (different substances) at once. The results obtained on the basis of the new model significantly increased their efficiency in relation to the models that were used earlier. Such an increase in all comparisons ranged from 3 to 12 %, and up to almost 94 %. If earlier it was possible to recognize only combinations of diagnoses in which there were no more than two diagnoses, then in this work for the first time it was possible to recognize three diagnoses at once. At the same time, the recognition efficiency became slightly more than 70 %. An attempt was also made to recognize more than three diagnoses, but the new model did not give significant results, slightly exceeding 50 % when recognizing four diagnoses at once.
Conclusions. Thanks to the use of Bayesian recognition procedures with independent signs, it was possible to significantly increase the recognition of inflammatory processes caused by brain cancer. The modified erythrocyte sedimentation rate, which is an auxiliary tool in the diagnosis of gliomas, allows one or another pathology to be determined in the preoperative period, since the pathology is finally determined only when studying a surgically removed tumor. In the postoperative period, such a modification is an indicator of repeated recurrence of gliomas. It was also possible to significantly increase the recognition of inflammatory processes caused by non-oncological disease (traumatic brain injury) in relation to oncological processes in gliomas, metastases and meningiomas. |
| format |
article |
| author |
Andrii Tarasov |
| author_facet |
Andrii Tarasov |
| author_sort |
Andrii Tarasov |
| title |
Bayesian Recognition Procedures with Independent Signs of Inflammatory Processes in Gliomas, Metastases and Meningiomas by Indicators of Erythrocyte Sedimentation Rate |
| title_short |
Bayesian Recognition Procedures with Independent Signs of Inflammatory Processes in Gliomas, Metastases and Meningiomas by Indicators of Erythrocyte Sedimentation Rate |
| title_full |
Bayesian Recognition Procedures with Independent Signs of Inflammatory Processes in Gliomas, Metastases and Meningiomas by Indicators of Erythrocyte Sedimentation Rate |
| title_fullStr |
Bayesian Recognition Procedures with Independent Signs of Inflammatory Processes in Gliomas, Metastases and Meningiomas by Indicators of Erythrocyte Sedimentation Rate |
| title_full_unstemmed |
Bayesian Recognition Procedures with Independent Signs of Inflammatory Processes in Gliomas, Metastases and Meningiomas by Indicators of Erythrocyte Sedimentation Rate |
| title_sort |
bayesian recognition procedures with independent signs of inflammatory processes in gliomas, metastases and meningiomas by indicators of erythrocyte sedimentation rate |
| publisher |
V.M. Glushkov Institute of Cybernetics |
| publishDate |
2021 |
| url |
https://doaj.org/article/799b047f1b9f4a2ca9a4d2bf80fa01ef |
| work_keys_str_mv |
AT andriitarasov bayesianrecognitionprocedureswithindependentsignsofinflammatoryprocessesingliomasmetastasesandmeningiomasbyindicatorsoferythrocytesedimentationrate |
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