A Study on Cross-Applicability and Potential of Machine Learning Tools in Hip and Dental Biomechanics
Abstract
Machine learning (ML) is transforming hip joint and dental biomechanics by analyzing complex data, identifying patterns, and improving diagnostics, treatment, and rehabilitation. Despite anatomical differences, both fields share fundamental biomechanical principles, particularly in hard tissue interactions under mechanical load. This study reviews research and explores the cross-applicability of ML tools in hip and dental biomechanics, including gait analysis, predictive modeling, multiscale modeling, and wear analysis. Leveraging shared principles through transfer learning, ML fosters cost-effective solutions and reduces the need for extensive data collection.
Details
- Organisation(s)
-
Institute of Mechanics and Computational Mechanics
Institute of Continuum Mechanics
Institute of Materials Science
- External Organisation(s)
-
Hannover Medical School (MHH)
- Type
- Contribution to book/anthology
- Pages
- 1-15
- No. of pages
- 15
- Publication date
- 02.01.2026
- Publication status
- Published
- Peer reviewed
- Yes
- ASJC Scopus subject areas
- General Engineering, General Mathematics
- Electronic version(s)
-
https://doi.org/10.1007/978-3-031-93213-7_1 (Access:
Closed
)
-
Details in the research portal "Research@Leibniz University"
Cite
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