AUTHOR=Chen Fang , Zhang Hao-Yi , Wan Yan-Long , Jia Jia-Nan , Wang Rui-Zhen , Gao Cheng , Chao Zhen-Yu , Ru Yu-Hua , Wang Zhe , Cheng Kai , Zhang Jiong , Feng Juan , Ren Jin-Ling , Ma Dong-Rui , Zhang Zhen-Qiang 

TITLE=Artificial intelligence-assisted organoid construction in congenital heart disease: current applications and future prospects

JOURNAL=Frontiers in Bioengineering and Biotechnology

VOLUME=Volume 13 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/bioengineering-and-biotechnology/articles/10.3389/fbioe.2025.1691972

DOI=10.3389/fbioe.2025.1691972

ISSN=2296-4185

ABSTRACT=Congenital heart disease (CHD) is a complex group of cardiac abnormalities arising during fetal development. Despite advancements in diagnostics and surgery, CHD mechanisms remain elusive due to inadequate disease models. Recent innovations in artificial intelligence (AI)-assisted organoid construction, which replicate tissue architecture and function, provide a promising in vitro platform for modeling cardiac development and CHD progression with high precision. This review summarizes AI-driven approaches in CHD organoid construction, focusing on machine learning (ML) applications in self-assembly, three-dimensional (3D) bioprinting, tissue engineering, and microfluidic organ-on-a-chip (OOC) technologies. We also discuss refinements in AI algorithms - such as support vector machines (SVMs), decision trees, and neural networks - to enhance cell-cell interaction analysis, optimize drug screening, and improve toxicity/efficacy assessments. Looking ahead, AI is poised to accelerate CHD organoid translation to clinical practice, advancing precision medicine.