AI Models for Multiplexed Detection of Microbial Toxins Using Nanoplasmonics

AI Models for Multiplexed Detection of Microbial Toxins Using Nanoplasmonics

Authors- Simreena

Abstract--The precise and rapid identification of microbial toxins is vital in managing infectious diseases, ensuring food and water safety, and protecting public health. Nanoplasmonic biosensors have emerged as promising tools due to their sensitivity, specificity, and label-free operation. However, as these platforms are scaled for multiplexed detection—simultaneously targeting multiple toxins—the complexity of signal interpretation grows significantly. Artificial intelligence (AI), particularly through machine learning and deep learning techniques, provides a solution for deciphering the intricate spectral patterns produced during multiplexed assays. This article explores the synergy between AI and nanoplasmonic sensing technologies to enable efficient, real-time, and high-throughput detection of microbial toxins.

DOI: /10.61463/ijset.vol.13.issue2.429