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Machine Learning Assists in the Design and Application of Microneedles

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Udgivet i:Biomimetics vol. 9, no. 8 (2024), p. 469
Hovedforfatter: He, Wenqing
Andre forfattere: Kong, Suixiu, Lin, Rumin, Xie, Yuanting, Zheng, Shanshan, Yin, Ziyu, Huang, Xin, Su, Lei, Zhang, Xueji
Udgivet:
MDPI AG
Fag:
Machine learning
Design optimization
Accuracy
Artificial intelligence
Deep learning
Datasets
Back propagation
Drug delivery systems
Medical technology
Neural networks
Classification
Biosensors
Medical equipment
Skin diseases
Algorithms
Clustering
Decision trees
Concept learning
Learning algorithms
Product development
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Resumen: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.
ISSN:2313-7673
DOI:10.3390/biomimetics9080469
Fuente:Biological Science Database