Orthodontic Facial Soft Tissue Prediction: A Bibliometric Analysis of Global Research Trends and Hotspots
Year: 2025
Type: preprint
Abstract: The field of orthodontic facial soft tissue prediction is a cornerstone of modern treatment planning, aiming to achieve both functional and aesthetic harmony for patients. Driven by advancements in three-dimensional imaging, computational modeling, and artificial intelligence, this domain has seen significant growth and methodological evolution. However, a comprehensive, macro-level overview of global research trends and thematic hotspots remains elusive. To address this, a bibliometric analysis was conducted to systematically map the intellectual structure of this critical area. The study aims to quantitatively delineate key research themes, identify influential contributors, and visualize the collaborative networks and thematic shifts within the field. By employing specialized bibliometric software to analyze a robust dataset from major databases, this review provides a foundational, evidence-based portrait of the research landscape. The findings are expected to offer invaluable insights for researchers and clinicians, guiding future investigations and strategic collaborations to further refine the science of facial soft tissue prediction.
Source: OSF Preprints (OSF Preprints)
Author: Yiyin Zhang
Language: English
Subfield: Orthodontics
Field: Dentistry
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W6887688431
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