基于计算机视觉的人工智能介导的编码-解码用于多重微流控数字免疫分析。
Computer Vision-Based Artificial Intelligence-Mediated Encoding-Decoding for Multiplexed Microfluidic Digital Immunoassay.
机构信息
College of Food Science and Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei China.
College of Engineering, Huazhong Agricultural University, Wuhan, 430070, Hubei China.
出版信息
ACS Nano. 2023 Jul 25;17(14):13700-13714. doi: 10.1021/acsnano.3c02941. Epub 2023 Jul 17.
Digital immunoassays with multiplexed capacity, ultrahigh sensitivity, and broad affordability are urgently required in clinical diagnosis, food safety, and environmental monitoring. In this work, a multidimensional digital immunoassay has been developed through microparticle-based encoding and artificial intelligence-based decoding, enabling multiplexed detection with high sensitivity and convenient operation. The information encoded in the features of microspheres, including their size, number, and color, allows for the simultaneous identification and accurate quantification of multiple targets. Computer vision-based artificial intelligence can analyze the microscopy images for information decoding and output identification results visually. Moreover, the optical microscopy imaging can be well integrated with the microfluidic platform, allowing for encoding-decoding through the computer vision-based artificial intelligence. This microfluidic digital immunoassay can simultaneously analyze multiple inflammatory markers and antibiotics within 30 min with high sensitivity and a broad detection range from pg/mL to μg/mL, which holds great promise as an intelligent bioassay for next-generation multiplexed biosensing.
多维数字免疫分析通过基于微球的编码和基于人工智能的解码得以实现,具有高灵敏度和操作便捷的特点,可实现多重检测。微球的特征(包括大小、数量和颜色)中所编码的信息可以同时识别和准确量化多个目标。基于计算机视觉的人工智能可以分析显微镜图像以进行信息解码,并直观地输出识别结果。此外,光学显微镜成像可以与微流控平台很好地集成,通过基于计算机视觉的人工智能进行编码-解码。这种微流控数字免疫分析可以在 30 分钟内同时分析多种炎症标志物和抗生素,具有高灵敏度和从 pg/mL 到 μg/mL 的宽检测范围,有望成为下一代多重生物传感的智能生物分析方法。