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机器学习可以促进三维生物打印.

Hongwei Ning1, Teng Zhou2, Sang Woo Joo3

  • 1College of Information and Network Engineering, Anhui Science and Technology University, Bengbu, Anhui, China.

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|June 16, 2023
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概括
此摘要是机器生成的。

机器学习通过优化生物墨水和打印参数来增强三维 (3D) 生物打印. 这种整合提高了准确性,并减少了细胞损伤,推进了组织工程应用.

关键词:
增材制造 增材制造是一种增材制造.生物打印是一种生物打印技术.组合学习学习 组合学习K-最近的邻居长期短期记忆 长期短期记忆

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科学领域:

  • 生物技术是生物技术.
  • 材料科学 材料科学 材料科学
  • 计算机科学 计算机科学

背景情况:

  • 三维 (3D) 生物打印是一种用于创建生物结构的增材制造技术.
  • 目前面临的挑战包括选择合适的生物墨水和提高印刷精度.
  • 细胞损伤和细胞死亡是生物打印过程中的重大问题.

研究的目的:

  • 审查机器学习 (ML) 与3D生物打印的整合.
  • 探索ML在应对当前生物打印挑战中的作用.
  • 总结一下最近在机器学习驱动的生物墨水开发,参数优化和缺陷检测方面的进展.

主要方法:

  • 对适用于生物打印的机器学习算法的审查.
  • 分析ML在增材制造中的作用.
  • 对3D生物打印中的ML应用研究的综合,用于生物墨水生成,参数优化和缺陷检测.

主要成果:

  • 机器学习算法为行为预测和模型探索提供预测能力.
  • ML有助于识别高效的生物墨水和优化打印参数.
  • 在3D生物打印过程中,ML有助于检测缺陷.

结论:

  • 机器学习和3D生物打印的结合显示出对推进组织工程的重大前景.
  • 机器学习可以克服生物墨水选择,印刷精度和工艺监控方面的关键局限性.
  • 预计在这个跨学科领域的进一步研究将产生创新的解决方案.