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Carbon dots meet artificial intelligence: applications in biomedical engineering
Yalei Guo1, Yige Liu2, Jiajin Yang1
1State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, Department of Head and Neck Oncology, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, Sichuan, China. zhiyongguo@scu.edu.cn.
Abstract:
Carbon dots (CDs) are fluorescent carbon nanomaterials typically less than 10 nm in size with excellent water solubility, low toxicity, high biocompatibility, favorable optical properties, and modifiable surface. CDs have great promise in various fields, including bioimaging, sensing, and drug delivery. With the emergence of artificial intelligence (AI) technologies, particularly machine learning (ML) and deep learning (DL) algorithms, new avenues for synthesis optimization, performance improvement, and accurate detection and diagnosis using CDs in biomedical engineering have been opened up. This article aims to present a comprehensive review of the applications of AI in CD research, from material design and performance optimization to material characterization and data analysis. It also addresses the possible areas of application for AI-assisted CDs in biomedical engineering, highlighting the importance and future directions of this interdisciplinary area of research. In addition, the potential role of CDs in advancing AI technologies such as optoelectronic storage devices and neuromorphic computing is explored, as well as the lasting impact of the convergence of CDs and AI on the future course of technological advancement.

