Scoliosis Research Trends and the Role of Artificial Intelligence: A Latent Dirichlet Allocation Analysis of Publications (2000–2024)
DOI:
https://doi.org/10.66588/NCMR.3.2.03Keywords:
Latent dirichlet allocation, Scoliosis, Topic modeling, Artificial intelligenceAbstract
This study aimed to evaluate global research trends in scoliosis between 2000 and 2024 using latent Dirichlet allocation (LDA) topic modeling. English-language, peer-reviewed journal articles indexed in Scopus were analyzed using their titles, abstracts and keywords to identify dominant and relatively underrepresented research themes. The findings showed that surgery-related topics accounted for the largest thematic proportion of the scoliosis literature, whereas etiopathogenesis and genetic factors had limited structural representation. Artificial intelligence-related studies increased in recent years but remained primarily focused on radiological assessment, Cobb angle measurement and diagnostic applications. These results demonstrate an imbalance in the thematic distribution of scoliosis research; however, bibliometric frequency and topic proportion should not be interpreted as direct indicators of scientific quality or clinical importance. The findings may help researchers recognize areas that warrant further investigation, particularly etiological and genetic mechanisms. The application of artificial intelligence in genetics, precision medicine and treatment planning should be regarded as a potential direction for future research rather than an outcome directly demonstrated by the present analysis.
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