Xinyi Liang, Hayoung Kim, Thanh Mien Nguyen, Kun Wang, Cheng Li, Seunghyun Lee, Jingbin Zeng, Jaebum Choo
colourimetric, fluorescence, chemiluminescence, surface-enhanced Raman scattering, photothermal, and electrochemical), thereby enabling intrinsic cross-verification and expanding diagnostic reliability. Parallel advances in AI, smartphone integration, and the Internet of Things connectivity have further elevated LFAs into digitally networked biosensors where embedded algorithms perform automated signal interpretation, error correction, and multi-mode data fusion, while cloud-linked infrastructures enable remote monitoring and epidemiological intelligence. These developments collectively reframe LFAs as integral components of data-driven, personalised, and preventive healthcare systems. Herein, we provide a unified framework that links design-on-demand MMNP synthesis, fully automated microfluidic LFA devices, AI-enhanced clinical decision support, and regulatory standardisation, and outline strategies for translating next-generation intelligent LFAs from laboratory innovation to global medical deployment.