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Войти в исследования Analytical cellular pathology (Amsterdam) · 2026
Machine Learning-Based Text Processing Reveals Research Trends in Heterotopic Ossification.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
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Sun Yangbai, Zhu Qinyuan, Yu Chaoran, Wang Chunmeng, Yan Wangjun, Jiang Chaoyin
Аннотация
BACKGROUND: Heterotopic ossification (HO) represents a highly active research field in pathological bone formation. Despite substantial advancements, a comprehensive understanding of its underlying mechanisms and clinical trajectory remains incomplete.
MATERIALS AND METHODS: A bibliometric and machine-learning latent Dirichlet allocation (LDA) analysis was performed using data retrieved from the Web of Science Core Collection database.
RESULTS: A total of 4722 publications related to HO were identified. The most prolific countries included the USA, CHINA, GERMANY, the UK, JAPAN, SOUTH KOREA, ITALY, TURKEY, FRANCE, and CANADA . GERMANY demonstrated the highest citation strength, followed by CHINA . Aside from "heterotopic ossification," other frequently occurring author keywords included "fibrodysplasia ossificans progressive," "complications" and "total hip arthroplasty." In keywords plus, besides HO, replacement, bone-formation, and arthroplasty were the most frequently occurring terms. Institutional network analysis with subject-specific clustering indicated that Shanghai Jiao Tong University was significantly enriched in radiology, nuclear medicine and medical imaging, while Wilderness Spine Serv specialized in surgical management. A developmental timeline plot of a network of most contributing authors also was visualized, along with the most influential references. Meanwhile, citation analysis indicated that Kaplan FS and Shore EM were the top-cited authors. By LDA analysis, a total of 16 key topics were identified in this field with distinct period-proportion visualization. One of the topics, cell bone express differentiation and formation has clearly dominated the last 10 years.
CONCLUSION: This study constitutes the most extensive text processing analysis of HO to date, offering valuable insights and directions for future development.
MATERIALS AND METHODS: A bibliometric and machine-learning latent Dirichlet allocation (LDA) analysis was performed using data retrieved from the Web of Science Core Collection database.
RESULTS: A total of 4722 publications related to HO were identified. The most prolific countries included the USA, CHINA, GERMANY, the UK, JAPAN, SOUTH KOREA, ITALY, TURKEY, FRANCE, and CANADA . GERMANY demonstrated the highest citation strength, followed by CHINA . Aside from "heterotopic ossification," other frequently occurring author keywords included "fibrodysplasia ossificans progressive," "complications" and "total hip arthroplasty." In keywords plus, besides HO, replacement, bone-formation, and arthroplasty were the most frequently occurring terms. Institutional network analysis with subject-specific clustering indicated that Shanghai Jiao Tong University was significantly enriched in radiology, nuclear medicine and medical imaging, while Wilderness Spine Serv specialized in surgical management. A developmental timeline plot of a network of most contributing authors also was visualized, along with the most influential references. Meanwhile, citation analysis indicated that Kaplan FS and Shore EM were the top-cited authors. By LDA analysis, a total of 16 key topics were identified in this field with distinct period-proportion visualization. One of the topics, cell bone express differentiation and formation has clearly dominated the last 10 years.
CONCLUSION: This study constitutes the most extensive text processing analysis of HO to date, offering valuable insights and directions for future development.