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DC Field | Value | Language |
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dc.contributor.author | Chen, H | - |
dc.contributor.author | Zhang, B | - |
dc.contributor.author | Huang, J | - |
dc.date.accessioned | 2024-09-14T08:37:25Z | - |
dc.date.available | 2024-09-14T08:37:25Z | - |
dc.date.issued | 2024-07-19 | - |
dc.identifier | ORCiD: Hongyi Chen https://orcid.org/0000-0001-8241-6648 | - |
dc.identifier | ORCiD: Bin Zhang https://orcid.org/0000-0003-2374-0127 | - |
dc.identifier | ORCiD: Jie Huang https://orcid.org/0000-0001-7951-2217 | - |
dc.identifier | 031301 | - |
dc.identifier.citation | Chen, H., Zhang, B. and Huang, J. (2024) 'Recent advances and applications of artificial intelligence in 3D bioprinting', Biophysics Reviews, 5 (3), 031301. doi: 10.1063/5.0190208. | en_US |
dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/29737 | - |
dc.description.abstract | 3D bioprinting techniques enable the precise deposition of living cells, biomaterials, and biomolecules, emerging as a promising approach for engineering functional tissues and organs. Meanwhile, recent advances in 3D bioprinting enable researchers to build in vitro models with finely controlled and complex micro-architecture for drug screening and disease modeling. Recently, artificial intelligence (AI) has been applied to different stages of 3D bioprinting, including medical image reconstruction, bioink selection, and printing process, with both classical AI and machine learning approaches. The ability of AI to handle complex datasets, make complex computations, learn from past experiences, and optimize processes dynamically makes it an invaluable tool in advancing 3D bioprinting. The review highlights the current integration of AI in 3D bioprinting and discusses future approaches to harness the synergistic capabilities of 3D bioprinting and AI for developing personalized tissues and organs. | en_US |
dc.description.sponsorship | B.Z. would like to thank Royal Society Research Grant (The Royal Society 10.13039/501100000288, RG\R1\241133) for supporting the research work and collaborations. | en_US |
dc.format.medium | Electronic | - |
dc.language.iso | en_US | en_US |
dc.publisher | AIP Publishing | en_US |
dc.rights | Copyright © 2024 Author(s). Published under an exclusive license by AIP Publishing. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics. The following article appeared in Chen, H., Zhang, B. and Huang, J. (2024) 'Recent advances and applications of artificial intelligence in 3D bioprinting', Biophysics Reviews, 5 (3), 031301, and may be found at https://doi.org/10.1063/5.0190208 (see: https://publishing.aip.org/resources/researchers/rights-and-permissions/sharing-content-online/ ). | - |
dc.rights.uri | https://publishing.aip.org/resources/researchers/rights-and-permissions/sharing-content-online/ | - |
dc.subject | 3D bioprinting | en_US |
dc.subject | hydrogel materials | en_US |
dc.subject | artificial intelligence | en_US |
dc.subject | machine learning | en_US |
dc.title | Recent advances and applications of artificial intelligence in 3D bioprinting | en_US |
dc.type | Article | en_US |
dc.date.dateAccepted | 2024-06-11 | - |
dc.identifier.doi | https://doi.org/10.1063/5.0190208 | - |
dc.relation.isPartOf | Biophysics Reviews | - |
pubs.issue | 3 | - |
pubs.publication-status | Published | - |
pubs.volume | 5 | - |
dc.identifier.eissn | 2688-4089 | - |
dc.rights.holder | American Institute of Physics | - |
Appears in Collections: | Dept of Mechanical and Aerospace Engineering Research Papers |
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File | Description | Size | Format | |
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FullText.pdf | Copyright © 2024 Author(s). Published under an exclusive license by AIP Publishing. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics. The following article appeared in Chen, H., Zhang, B. and Huang, J. (2024) 'Recent advances and applications of artificial intelligence in 3D bioprinting', Biophysics Reviews, 5 (3), 031301, and may be found at https://doi.org/10.1063/5.0190208 (see: https://publishing.aip.org/resources/researchers/rights-and-permissions/sharing-content-online/ ). | 1.05 MB | Adobe PDF | View/Open |
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