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◆ Trends in biotechnology2026-03-01· Organoid

Next-generation discovery: empowering organoid research with machine learning, artificial intelligence, and mathematical modeling

Sneha Pushpa Ramesan, Jasmitha Boovadira Poonacha, Dilan Pathirana, Simon Jens Merkt, Christian Maaß, Jan Hasenauer, Elena S. Reckzeh

原始摘要(英文原文)· Original abstract
Organoids have rapidly matured into powerful model systems. The field is pushing organoids toward architectural sophistication and functional fidelity, with longitudinal experiments producing ever-larger and more complex datasets. As a result, computational methods have become indispensable for experimental design, data analysis, and predictive modeling, as well as for obtaining mechanistic insights. In this review, we survey recent progress at the interface of organoid research and computational approaches, discuss key challenges on both fronts, and outline future directions to maximize impact in biomedical research through convergent, synergistic efforts.
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Next-generation discovery: empowering organoid research with machine learning, artificial intelligence, and mathematical modeling — 科研速览 Science Skim