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Other literature type . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Other literature type . 2025
License: CC BY
Data sources: Datacite
ZENODO
Other literature type . 2025
License: CC BY
Data sources: Datacite
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OPTIMIZATION OF METHODS FOR THE DIAGNOSIS AND TREATMENT OF ORAL MUCOSAL DISEASES

Authors: Azizabonu Kodirova, Dilnoza Khasanova;

OPTIMIZATION OF METHODS FOR THE DIAGNOSIS AND TREATMENT OF ORAL MUCOSAL DISEASES

Abstract

Diseases of the oral mucosa represent one of the most common pathologies in dental practice. The diagnosis of such conditions requires a comprehensive approach, including clinical, laboratory, and instrumental examinations. The aim of this study is to develop and implement optimized methods for the diagnosis and treatment of oral mucosal diseases using modern technologies and a personalized approach. Based on the analysis of 120 clinical cases, the effectiveness of various diagnostic methods (cytology, PCR analysis, dermatoscopy) and treatment regimens (anti-inflammatory, antiseptic, and immunostimulating agents) was evaluated. The results showed that a comprehensive approach increases diagnostic accuracy and improves clinical outcomes in patients.

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average