How Artificial Intelligence manage biomaterial for scaffold production in stem cell research

Background and Aims: Artificial intelligence (AI) has emerged as a transformative force across various fields, particularly in tissue engineering and stem cell research. Its significant contributions include the optimization of biomaterials and scaffold development for tissue engineering applications. This study aims to explore the role of AI techniques, specifically machine learning and deep learning, in enhancing the behavior of stem cells and improving scaffold design. Methods: AI was utilized to control stem cell behaviors such as migration, adhesion, and differentiation, which are directly influenced by the properties of the scaffolds. Researchers modified several parameters, including biomaterial types, components, manufacturing processes, and scaffold geometries, to investigate their effects on cellular fate. Additionally, AI algorithms were employed for image analysis to characterize scaffold properties like morphology, porosity, and cell adhesion, utilizing diverse data types including tabular, image, and video data. Results: The application of AI demonstrated a significant ability to optimize scaffold design and enhance characterization techniques. The predictive capabilities of AI allowed for the forecasting of cell behavior and culturing outcomes, effectively reducing experimental workloads. Furthermore, AI-guided modifications led to improved cell-scaffold interactions, suggesting enhanced efficacy in tissue engineering applications. Conclusion: The integration of AI in biomaterial research and tissue engineering holds great promise for advancing personalized medicine approaches, enabling the creation of tailored scaffolds that cater to specific patient needs. As AI technology continues to evolve, its applications in biomaterials and tissue engineering are expected to expand, potentially revolutionizing the field. The findings underscore the importance of AI in optimizing scaffold design and improving the management of stem cell behaviors, paving the way for more effective tissue engineering solutions.

کلیدواژه ها:

Artificial Intelligence ، Stem Cell ، Tissue Engineering