A review on the applications of machine learning in biomaterials, biomechanics, and biomanufacturing for tissue engineering

Q1 Engineering
RenKai Fu , Zhenghong Chen , Hua Tian , Jiajie Hu , Fangxin Bu , Peng Zheng , Liang Chi , Lulu Xue , Qing Jiang , Lan Li , Liya Zhu
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引用次数: 0

Abstract

In recent years, machine learning, a powerful data analysis and modeling technique, is continuously revolutionizing the field of tissue engineering. Its ability to learn and extract information from complex datasets opens up new opportunities for the development of tissue engineering. In this paper, we first provide a categorized overview of different types of machine learning algorithms, and then focus on the recent advances in the application of machine learning in tissue engineering. We summarize the technology's latest applications in biomaterials, biomechanics, and biomanufacturing, discuss the challenges faced, and explore future prospects aiming at providing scientific references for researchers to achieve further progress in the fields of tissue engineering and machine learning.

Abstract Image

综述了机器学习在组织工程生物材料、生物力学和生物制造中的应用
近年来,机器学习作为一种强大的数据分析和建模技术,正在不断革新组织工程领域。它从复杂数据集中学习和提取信息的能力为组织工程的发展开辟了新的机会。在本文中,我们首先对不同类型的机器学习算法进行了分类概述,然后重点介绍了机器学习在组织工程中的应用的最新进展。总结了该技术在生物材料、生物力学和生物制造等领域的最新应用,讨论了面临的挑战,并探讨了未来的前景,旨在为研究人员在组织工程和机器学习领域取得进一步进展提供科学参考。
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来源期刊
Smart Materials in Medicine
Smart Materials in Medicine Engineering-Biomedical Engineering
CiteScore
14.00
自引率
0.00%
发文量
41
审稿时长
48 days
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