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Article . 2025 . Peer-reviewed
License: CC BY
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Article . 2025
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Artificial Intelligence for Organoids Multidimensional Assessment

Authors: Yulin Mo; Jian Wang; Huijian Yang; Long Bai; Ke Xu; Jiacan Su;

Artificial Intelligence for Organoids Multidimensional Assessment

Abstract

ABSTRACTOrganoids are tissue analogues formed through in vitro three‐dimensional culture of stem cells, possessing specific spatial structures. Organoids have become integral to various biomedical fields, including disease pathogenesis, model construction, regenerative and precision medicine, drug screening, tissue and organ development, toxicology, and pathological analysis. However, the diversity of organoid types and variations in their production processes have led to inconsistencies in their application for assessment and analysis. To date, no comprehensive standards or guidelines for evaluating organoids have been established. Artificial intelligence (AI) technology is extensively employed in biomedical image analysis, data processing, and molecular structure prediction, demonstrating benefits in the assessment of organoids. This review will examine the application of AI across various aspects of organoid assessment, such as omics, histology, morphology, functional properties, and drug screening, with the goal of offering new perspectives on organoid assessment.

Related Organizations
Keywords

assessment, TA401-492, drug screening, artificial intelligence, single‐cell sequencing, Materials of engineering and construction. Mechanics of materials, organoids

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    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).
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    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.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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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!
3
Top 10%
Average
Average
gold
Related to Research communities