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Updated: May 10, 2025

Automated Robotic Dispensing Technique for Surface Guidance and Bioprinting of Cells

Automated Robotic Dispensing Technique for Surface Guidance and Bioprinting of Cells

Published on: November 18, 2016

机器学习增强优化用于高通量精度的细胞液滴生物打印.

Jaemyung Shin¹, Ryan Kang², Kinam Hyun³

¹Department of Biomedical Engineering, Schulich School of Engineering, University of Calgary, Calgary, Alberta, T2N 1N4, Canada.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)

|April 27, 2025

概括

此摘要是机器生成的。

机器学习优化了3D生物打印参数,用于一致的有机体生产,克服了手工方法.

关键词:

生物打印是一种生物打印技术.细胞滴滴滴滴滴滴滴滴滴滴滴机器学习是机器学习.优化的优化优化优化.

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Last Updated: May 10, 2025

Automated Robotic Dispensing Technique for Surface Guidance and Bioprinting of Cells

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Published on: November 18, 2016

Viability of Bioprinted Cellular Constructs Using a Three Dispenser Cartesian Printer

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Published on: September 22, 2015

Counting Proteins in Single Cells with Addressable Droplet Microarrays

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科学领域:

生物技术和生物医学工程生物技术和生物医学工程

背景情况:

使用手工管道的传统有机体生产方法是劳动密集型的,容易产生批量变化.
3D生物打印为一致的有机体生产提供了更有效的替代方案,但参数优化具有挑战性.

研究的目的:

使用机器学习来优化有机体生产的关键3D生物打印参数.
根据打印参数开发算法,立即预测基于打印参数的细胞液滴大小.

主要方法:

设计了一种高通量细胞液滴生物打印机,能够同时打印50多个液滴.
利用机器学习优化五个参数:生物墨水粘度,喷嘴大小,打印时间,打印压力和细胞度.
评估了五种机器学习算法,包括多层感知器和决策树模型.

主要成果:

多层感知子模型实现了对细胞滴滴大小的最高预测准确度.
决策树模型在评估算法中提供了最快的计算时间.
开发了一个用户友好的界面,整合了优化的机器学习模型.

结论:

机器学习有效地优化了3D生物打印参数,用于可复制的有机体生产.
开发的平台简化了有机物生成,使可扩展的生产用于各种应用.
预计这种方法将与各种生物打印技术产生协同作用.