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https://doi.org/10.5772/intech...
Part of book or chapter of book . 2024 . Peer-reviewed
License: CC BY
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Organoid Intelligence: Bridging Artificial Intelligence for Biological Computing and Neurological Insights

Authors: Sangeeta Ballav; Amit Ranjan; Shubhayan Sur; Soumya Basu;

Organoid Intelligence: Bridging Artificial Intelligence for Biological Computing and Neurological Insights

Abstract

Brain organoid implications have opened vast avenues in the realm of interdisciplinary research, particularly in the growing field of organoid intelligence (OI). A brain organoid is a three-dimensional (3D), lab-grown structure that mimics certain aspects of the human brain organization and function. The integration of organoid technology with computational methods to enhance the understanding of organoid behavior and to predict their responses to various stimuli is known as OI. The ability of brain organoids to adapt and memorize, is a key area of exploration. OI encapsulates the confluence of breakthroughs in stem cell technology, bioengineering, and artificial intelligence (AI). This chapter delves deep into the myriad potentials of OI, encompassing an enhanced understanding of human cognitive functions, and achieving significant biological computational proficiencies. Such advancements stand to offer a unique complementarity to conventional computing methods. The implications of brain organoids in the OI sphere signify a transformative stride towards a more intricate grasp of the human brain and its multifaceted intricacies. The intersection of biology and machine learning is a rapidly evolving field that is reshaping our understanding of life and health. This convergence is driving advancements in numerous areas, including genomics, drug discovery, personalized medicine, and synthetic biology.

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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).
    4
    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).
    Average
    impulse
    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!
4
Top 10%
Average
Average
hybrid
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