Point-of-care (POC) nanosensors with high screening efficiency show promise for user-friendly manipulation in the ever-increasing on-site analysis demand for illness diagnosis, environmental monitoring, and food safety. Currently, inspired by the merits of integrating advanced nanomaterials, molecular biology, machine learning, and artificial intelligence, lateral flow immunoassay (LFIA)-based POC nanosensors have been devoted to satisfying the commercial demands in terms of sensitivity, specificity, and practicality. Herein, we examine the use of multidimensional enhanced LFIA in various fields over the past two decades, focusing on introducing advanced nanomaterials to improve the acquisition capability of small order of magnitude targets through engineering transformations and emphasizing interdomain fusion to collaboratively address the inherent challenges in current commercial applications, such as multiplexing, development of detectors for quantitative analysis, more practical on-site monitoring, and sensitivity enhancement. Specifically, this comprehensive review encompasses the latest advances in comprehending LFIA with an alternative signal transduction pattern, aiming to achieve rapid, ultrasensitive, and "sample-to-answer" available options with progressive applications for POC nanosensors. In summary, through the cross-collaboration development of disciplines, LFIA has the potential to break the barriers toward commercialization and achieve laboratory-level POC nanosensors, thus leading to the emergence of the next generation of LFIA.
Keywords: Artificial Intelligence; Detector; Lateral Flow Immunoassay; Multiplexing; Nanomaterials; Point-of-Care; Practicability; Signal Transduction.