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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.

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A Study on Cross-Applicability and Potential of Machine Learning Tools in Hip and Dental Biomechanics

  • 章节

  • 发表日期：

    2025年

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  • Fadi Aldakheel,
  • Yousef Heider,
  • Marco Haertlé,
  • Peter Wriggers,
  • Hans Jürgen Maier,
  • Meike Stiesch

摘要

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.