AI-Integrated Micro/Nanorobots for Biomedical Applications: Recent Advances in Design, Fabrication, and Functions.

Area of Science:

• Biomedical Engineering
• Artificial Intelligence
• Nanotechnology

Background:

• Micro/nanorobotics and AI integration is transforming biosensing.
• Miniaturized robots navigate biological environments for sensing and therapy.
• AI algorithms provide control and signal interpretation for biosensing.

Purpose of the Study:

• To review recent advances in AI-enabled micro/nanorobots for biomedical sensing.
• To highlight applications in diagnostics, in vivo sensing, and personalized medicine.
• To discuss challenges and future directions in the field.

Main Methods:

• Fabrication techniques including photolithography, soft lithography, nanoimprinting, 3D printing, and self-assembly.
• Integration of AI algorithms, machine learning (ML), and deep learning (DL) for autonomous operation.
• Review of current literature on AI-enabled micro/nanorobots in biosensing.

Main Results:

• AI-driven micro/nanorobots enable autonomous, adaptive, high-resolution biological analysis.
• Successful navigation and targeted actions in complex biological environments.
• Demonstrated potential in point-of-care diagnostics, in vivo sensing, and organ-on-chip systems.

Conclusions:

• AI-enabled micro/nanorobots represent a significant advancement in biosensing technology.
• These systems promise intelligent, responsive, and clinically transformative applications.
• Addressing challenges in scalability, energy, data, and control is crucial for future development.