Emerging nanosensor platforms and machine learning strategies toward rapid, point-of-need small-molecule metabolite detection and monitoring
Shi Xuan Leong, Yong Xiang Leong, Charlynn Sher Lin Koh, Emily Xi Tan, Lam Bang Thanh Nguyen, Jaslyn Ru Ting Chen, Carice Chong, Desmond Wei Cheng Pang, Howard Yi Fan Sim, Xiaochen Liang, Nguan Soon Tan, Xing Yi Ling
Abstract
chemical- and physical-based modification strategies, (2) development of hybrid techniques including multimodal and hyphenated techniques, and (3) synergistic use of machine learning such as clustering, classification and regression algorithms for data exploration and predictions. These concepts can be further integrated as multifaceted strategies to further boost nanosensor performances. Finally, we present a critical outlook that explores future opportunities toward the design of next-generation nanosensor platforms for rapid, point-of-need detection of various small-molecule metabolites.