商业化
计算机科学
环境监测
模式
数据科学
机器学习
人工智能
纳米技术
工程类
政治学
社会科学
环境工程
社会学
材料科学
法学
作者
Zhongzeng Zhou,Tailin Xu,Xueji Zhang
标识
DOI:10.1016/j.trac.2024.117613
摘要
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.
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