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Cyborg and Bionic Systems
Article . 2023 . Peer-reviewed
Data sources: Crossref
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Cyborg and Bionic Systems
Article . 2023
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Engineering In vitro Models: Bioprinting of Organoids with Artificial Intelligence

Authors: Hyungseok Lee;

Engineering In vitro Models: Bioprinting of Organoids with Artificial Intelligence

Abstract

In the last decade, organoids have gained popularity for developing mini-organs to support advancements in the study of organogenesis, disease modeling, and drug screening and, subsequently, in the development of new therapies. To date, such cultures have been used to replicate the composition and functionality of organs such as the kidney, liver, brain, and pancreas. However, depending on the experimenter, the culture environment and cell conditions may slightly vary, resulting in different organoids; this factor significantly affects their application in new drug development, especially during quantification. Standardization in this context can be achieved using bioprinting technology—an advanced technology that can print various cells and biomaterials at desired locations. This technology offers numerous advantages, including the manufacturing of complex three-dimensional biological structures. Therefore, in addition to the standardization of organoids, bioprinting technology in organoid engineering can facilitate automation in the fabrication process as well as a closer mimicry of native organs. Further, artificial intelligence (AI) has currently emerged as an effective tool to monitor and control the quality of final developed objects. Thus, organoids, bioprinting technology, and AI can be combined to obtain high-quality in vitro models for multiple applications.

Related Organizations
Keywords

Perspective, Q300-390, Cybernetics

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
69
Top 1%
Top 10%
Top 1%
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