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机器学习和3D生物打印

Jie Sun1, Kai Yao1,2, Jia An3,4

  • 1School of Advanced Technology, Xi'an Jiaotong-Liverpool University, Suzhou, China.

International journal of bioprinting
|June 16, 2023
PubMed
概括

机器学习 (ML) 通过优化流程和材料来改善组织结构来增强生物打印. 本综述分析了ML应用,强调了印刷稳定性,设计和细胞性能方面的进步,以期未来的创新.

关键词:
生物材料是一种生物材料.生物打印构建了生物打印的结构.生物打印是一种生物打印技术.深度学习是一种深度学习.机器学习 机器学习

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科学领域:

  • 生物材料工程 生物材料工程
  • 生物技术是生物技术.
  • 计算生物学 计算生物学

背景情况:

  • 生物打印使生物模拟结构和活组织结构的制造成为可能.
  • 机器学习 (ML) 提供了优化生物打印过程,材料和构建性能的潜力.
  • 需要对生物打印中的ML应用进行全面分析,以指导未来的发展.

研究的目的:

  • 收集,分析和分类生物打印中的ML应用.
  • 总结ML对生物打印过程和构造性能的影响.
  • 确定生物打印技术和结构设计中ML的未来方向.

主要方法:

  • 对生物打印中的ML发表文章的系统审查.
  • 机器学习方法的分类 (传统的机器学习和深度学习).
  • 在优化印刷工艺,材料特性和构造性能方面分析ML应用.

主要成果:

  • 传统的ML和深度学习 (DL) 都用于优化生物打印.
  • ML提高了打印稳定性,精度 (例如层叠) 和材料性能.
  • ML提高了生物打印结构设计和细胞性能.

结论:

  • 机器学习显著推进了生物打印,从而实现了更稳定,更可靠的工艺.
  • 机器学习集成可以提高生物打印结构的质量和性能.
  • 开发集成的工艺-材料-性能模型对于革新生物打印至关重要.