ArticleFrontiers in medicine2025
CT-based subchondral bone and clinical predictors of long-term total ankle arthroplasty outcomes.
Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Artificial Intelligence in Arthroplasty: A Comprehensive Structured Critical Review and Descriptive Evidence Map of Validation, Uncertainty, and Workflow Integration.Bioengineering (Basel, Switzerland) · 2026Review
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2 authors.
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Abstract
Objective: This study aimed to develop a machine learning-based predictive model for personalized long-term prognosis assessment in patients undergoing total ankle arthroplasty (TAA) by integrating preoperative computed tomography (CT)-derived subchondral bone structural parameters with clinical indicators. Methods: A retrospective cohort study involving 340 TAA patients was divided into training ( Results: Baseline characteristics showed no statistically significant differences between training and validation sets ( Conclusion: The RF model that incorporates preoperative CT-quantified subchondral bone parameters and clinical indicators effectively predicts long-term adverse outcomes in TAA patients. The top three predictive features identified are subchondral BMD, Tb. Sp, and preoperative talar necrosis volume.
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