基于机器学习的骨科生物材料设计与优化

doi:10.6040/j.issn.1671-7554.0.2024.1274

Abstract

Abstract: With the development of artificial intelligence, the application of machine learning in the field of orthopedic biomaterials is also increasing, which has great potential. This paper first introduced the basic types of machine lear-ning, algorithm selection for different target scenarios and its evaluation index. Secondly, the key chemical and physical parameters in the design process of different orthopedic biomaterials, and the training data set of machine learning were analyzed. Then, the specific applications of machine learning in metal biological materials, bioceramics implant materials, polymer biological materials and new materials for bioprinting were discussed in detail, and the advantages of machine learning in predicting material properties, optimizing manufacturing processes, and studying biocompatibility were demonstrated through cases. Orthopedic biomaterials are developing in the direction of multidisciplinary integration and intelligence, and machine learning, as a key technology in this development trend, will more efficiently promote material development and clinical application. Finally, this paper analyzed the crucial impediments that hinder the further application of machine learning in clinical research, and looksed forward to the broad prospect of machine learning in the field of orthopedic biomaterials optimization design. In conclusion, machine learning provides new ideas and methods for the design and optimization of orthopedic biomaterials.

Key words: Machine learning, Orthopedic biomaterials, Material design, Performance optimization, Smart materials

CLC Number:

R318.08

LIU Yu, HUO Yaya, GONG Cheng, LIANG Ting, LI Bin. Design and optimization of orthopedic biomaterials based on machine learning[J].Journal of Shandong University (Health Sciences), 2026, 64(2): 22-33.

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