He Wenqing, Kong Suixiu, Lin Rumin, Xie Yuanting, Zheng Shanshan, Yin Ziyu, Huang Xin, Su Lei, Zhang Xueji
Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen 518000, China.
School of Biomedical Engineering, Marshall Laboratory of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen 518060, China.
Biomimetics (Basel). 2024 Aug 2;9(8):469. doi: 10.3390/biomimetics9080469.
Microneedles (MNs), characterized by their micron-sized sharp tips, can painlessly penetrate the skin and have shown significant potential in disease treatment and biosensing. With the development of artificial intelligence (AI), the design and application of MNs have experienced substantial innovation aided by machine learning (ML). This review begins with a brief introduction to the concept of ML and its current stage of development. Subsequently, the design principles and fabrication methods of MNs are explored, demonstrating the critical role of ML in optimizing their design and preparation. Integration between ML and the applications of MNs in therapy and sensing were further discussed. Finally, we outline the challenges and prospects of machine learning-assisted MN technology, aiming to advance its practical application and development in the field of smart diagnosis and treatment.
微针（MNs）以其微米级的尖锐尖端为特征，能够无痛穿透皮肤，并且在疾病治疗和生物传感方面显示出巨大潜力。随着人工智能（AI）的发展，微针的设计和应用在机器学习（ML）的辅助下经历了重大创新。本综述首先简要介绍了机器学习的概念及其当前发展阶段。随后，探讨了微针的设计原理和制造方法，展示了机器学习在优化其设计和制备方面的关键作用。进一步讨论了机器学习与微针在治疗和传感应用之间的整合。最后，我们概述了机器学习辅助微针技术的挑战和前景，旨在推动其在智能诊断和治疗领域的实际应用和发展。
