ARTIFICIAL INTELLIGENCE IN DENTAL RADIOLOGY: A BIBLIOMETRIC ANALYSIS OF CURRENT TRENDS AND FUTURE PROSPECTS (PART 1)
DOI:
https://doi.org/10.11603/2311-9624.2025.4.15972Keywords:
prosthodontics, diagnostics, computed tomography, orthopantomography, artificial intelligence, bibliometric analysis, statistical analysis.Abstract
Abstract. Modern dentistry is undergoing a global digital transformation, where the quality of diagnostics directly determines the success of subsequent treatment. Over the past decades, radiological technologies have evolved from traditional film-based radiography to high-precision cone-beam computed tomography (CBCT), which has significantly improved the visualization of anatomical structures in the maxillofacial region. Predicting the prospects for the application of artificial intelligence (AI) in the diagnostic process in dentistry through the analysis of scientific sources devoted to this topic, as an indicator of the global dental scientific community’s interest in developing this strategy, represents a highly relevant issue. Aims: To evaluate the effectiveness of statistical analysis methods in identifying current trends and research directions in diagnostic radiological technologies in dentistry, and to assess the degree of integration of artificial intelligence (AI) solutions into clinical practice based on publication activity. Materials and Methods: An analysis of publications in the scientometric electronic database PubMed/MEDLINE was conducted using the keywords “orthopantomography and dentistry,” “computed tomography and dentistry,” as well as “orthopantomography, dentistry and artificial intelligence” and “computer tomography, dentistry and artificial intelligence” for the period from December 31, 2015, to December 31, 2025; separately for the periods from December 31, 2019, to December 31, 2025, and from December 31, 2024, to December 31, 2025; and also over 84 months broken down quarterly – four quarters (Q1, Q2, Q3, Q4) per year. Evaluation of the obtained results was performed using methods of statistical analysis: descriptive statistics and inferential statistics (correlation and regression analysis) with the application of time series analysis methods. Regression analysis was conducted to examine the dependence of the number of publications containing the keyword pairs “CT (computed tomography) + AI” and “OPTG (orthopantomogram) + AI” in dentistry on the quarter during the period 2022-2025. For this purpose, in the Origin package [OriginPro, Version 9.8.0.200, OriginLab Corporation, Northampton, MA, USA], the data were approximated by polynomial functions of various orders, as well as by exponential and power functions. Results. Over the 10-year period, we identified 18,976 sources related to “CT and dentistry” compared to 3,799 for “OPTG and dentistry” – nearly 5 times more. The trend toward an even greater increase in the number of publications concerning CT in dentistry persists over both the 5-year and the most recent 1-year periods, exceeding those for OPTG by 6.07 and 5.41 times, respectively. Dental researchers devote greater attention to the use of computed tomography (CT) in the diagnostic process. The number of studies dedicated to the diagnostic process without the use of artificial intelligence exceeds the number of studies involving AI by 26,6 times over the 10-year study period. During the 2022–2025 period, the number of publications involving the application of AI in dentistry increased significantly. Over the 2022–2025 period, there was a strong linear growth in publications on CT combined with AI: an average annual increase of approximately 18 articles per year (R² = 0.84), rising from about 20 articles in 2022 to 70 in 2025. In contrast, growth in the area of orthopantomography combined with AI was more moderate and nonlinear: an average annual increase of approximately 8 articles (R² = 0.65 for the linear model), but better described by a second-degree polynomial (R² = 0.67), increasing from roughly 20 articles in 2022 to 50 in 2025. AI is being implemented more actively in dental computed tomography, where the growth trend is more stable and intensive than in orthopantomography. Conclusions. 1. Bibliometric analysis can successfully identify and substantiate current trends and directions in the development of diagnostic technologies. 2. The results of the analysis showed that the current trend in dental radiology is computed tomography (CT). The use of artificial intelligence in diagnostic radiological technologies in dentistry is still in the developmental stage compared to the use of classical analysis of radiographic findings. 3. Despite the rapid integration of artificial intelligence technologies into the diagnostic process in dentistry, the use of classical methods of statistical analysis for assessing the reliability of obtained results will remain a priority in the near future.
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