Artificial Intelligence Based Quality Control in 3D Bio-printing

The fabrication of tissues and organs for regenerative medicine applications has advanced significantly in the field of 3D bio-printing. Many elements, including cells, bio-materials, and growth factors, must be integrated into the creation of functional and bio-compatible constructions; this can cause variability and printing problems. Artificial intelligence (AI) has been used as a tool for 3D bio-printing quality control to get around these problems. The accuracy, reprehensibility, and efficiency of the printing process are all discussed in this study along with the present level of AI in 3D bio-printing. The success rate of complex tissue engineering applications can be raised by using AI algorithms for real-time monitoring, feedback control, and error correction. This will help to optimize the bio-printing procedure. Additionally, combining AI with other cutting-edge technologies, including computer vision and machine learning, can make it possible for 3D bioprinting to employ more complex and automated quality control procedures. The use of AI quality control in 3D bioprinting can increase regulatory compliance and standardization while maintaining the security and effectiveness of printed components. Researchers can use AI algorithms to enhance the design of printing procedures and find potential sources of inaccuracy. The use of AI in 3D bioprinting does, however, come with significant difficulties, such as the requirement for high-quality data sets, the creation of reliable algorithms that can deal with the complexity of biological systems, and the moral questions raised by the application of AI in biomedical research. Tissue engineering could undergo a revolution, thanks to the inclusion of AI quality control in 3D bioprinting, which would also make it possible to create tailored and regenerative medicine treatments.