生物传感器
背景(考古学)
纳米技术
计算机科学
转化式学习
材料科学
人工智能
生物
心理学
古生物学
教育学
作者
Tuğba Akkaş,Mahshid Reshadsedghi,Mustafa Şen,Volkan Kılıç,Nesrin Horzum
标识
DOI:10.1002/adma.202504796
摘要
Abstract Integrating artificial intelligence (AI) into biosensor technology enables data processing, quantitative analysis, real‐time decision‐making, and adaptive sensing capabilities through advanced pattern recognition and predictive modeling. In addition, AI has the potential to drive innovation in the design of advanced materials for biosensing applications by reducing the reliance on trial‐and‐error methods. This review explores the transformative impact of AI on biosensor technology in the context of historical development, current status, and future prospects. It begins with an overview of the evolution of AI, biosensor technology, and their integration. Comparative analysis of AI‐driven innovations in optical, fluorometric, and electrochemical biosensors is presented, highlighting how AI can improve sensor performance. The role of advanced materials on the development of AI‐assisted biosensors is also discussed as the choice of material has a profound effect on biosensor capabilities. Applications of AI‐assisted biosensors are comprehensively explored across healthcare, environmental monitoring, food safety, and agriculture. This study concludes by addressing challenges, opportunities, ethical concerns, and future research directions, providing a comprehensive and up‐to‐date resource for researchers.
科研通智能强力驱动
Strongly Powered by AbleSci AI