1. Empowerment of AI algorithms in biochemical sensors.
- Author
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Zhou, Zhongzeng, Xu, Tailin, and Zhang, Xueji
- Subjects
- *
ARTIFICIAL intelligence , *DETECTORS , *ALGORITHMS , *MULTIDIMENSIONAL databases , *ENVIRONMENTAL protection , *MEDICAL screening - Abstract
Biochemical sensors have become indispensable tools for real-time, on-site monitoring and analysis in diverse domains such as healthcare, environmental protection, and food safety. The rapid evolution of artificial intelligence (AI) has opened new frontiers for enhancing the capabilities of these sensors across a spectrum of detection modalities. This paper delves into the recent integration of AI algorithms into biochemical sensors, examining this advancement from a functional standpoint and focusing on the empowerments it brings to electrochemical, electrochemiluminescence, colorimetric, and Raman sensors. AI techniques aim to enhance the capabilities of biochemical sensors beyond traditional techniques and have enabled improved selectivity, drift correction, efficiency, resolution, assisted diagnosis, and biomarker screening from complex multidimensional data. In the end, we provide a personal perspective on future development and address the remaining challenges in the commercialization of AI-based biochemical sensors. • We introduce the common types and functions of AI algorithms used in biochemical sensors. • AI algorithms enhance biochemical sensors' performance, achieving highly sensitive, precise, and high-throughput analysis. • AI-assisted sensors unlock tremendous benefits across healthcare, environmental protection, and food safety. • A personal perspective on the challenges and future opportunities is discussed. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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