До питання трендів цифровізації у пародонтологічній практиці: аналіз сучасних концепцій та особливостей практичної імплементації

Oksana Shekera; Anatolii Palchykov; Myroslav Goncharuk-Khomyn

doi:10.33295/1992-576X-2026-2-CTDN-1

Authors

Oksana Shekera Uzhhorod National University https://orcid.org/0000-0002-3584-1024
Anatolii Palchykov Uzhhorod National University https://orcid.org/0000-0001-5565-6224
Myroslav Goncharuk-Khomyn Uzhhorod National University https://orcid.org/0000-0002-7482-3881

DOI:

https://doi.org/10.33295/1992-576X-2026-2-CTDN-1

Keywords:

periodontology, digital dentistry, digitalization, clinical practice, artificial intelligence, patient-centered care, evidence-based medicine

Abstract

Background. The capabilities of modern computational algorithms integrated into dedicated software solutions—whether standalone or coupled with specific hardware components such as intraoral scanners, cone-beam computed tomography, and automated periodontal diagnostic systems—are transforming the paradigms of digital technology implementation in periodontal practice.

Objective. To analyze current digitalization trends in periodontal practice, with a focus on modern concepts of big data processing and the individualization of comprehensive diagnostic and treatment approaches.

Materials and Methods. Dedicated search for relevant publications was conducted within the PubMed/MEDLINE and Scopus databases, as well as using the Google Scholar search engine, applying Boolean operators (AND, OR, NOT) and combinations of relevant keywords. During the process of content analysis with corresponding results’ structuring and grouping, all selected sources were categorized into the following analytical domains: level of actual clinical integration of digital technologies; role of artificial intelligence algorithms in periodontal-oriented diagnosis and prediction; multimodal data integration as a key trend in digitalization; barriers to implementation, prospects for development, and translation of digitalization into clinical periodontal practice.

Results. The current state of digitalization in periodontal practice is characterized by an imbalance between the rapid development of technological capabilities and the limited level of their clinical implementation. Despite the proven potential of artificial intelligence algorithms for processing multimodal data, improving diagnostic accuracy, risk stratification, and treatment outcome prediction in periodontology, their widespread implementation is limited by insufficient external validation, the heterogeneity and limited size of available datasets, variability in model performance depending on input data modalities, and the lack of standardized protocols for integration into clinical practice.

Conclusions. Digitalization in periodontal practice is characterized by a cluster pattern of implementation, primarily covering the diagnostic component and the initial classification of clinical cases. This is associated with both the statistical “maturity” of verification algorithms and the experience of their integration into relevant hardware and software systems. At the same time, the prognostic component, represented by algorithms for processing primary digital or digitized data obtained during patient diagnostics, remains the subject of ongoing validation studies, the number of which is steadily increasing.

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