AI-driven lateral flow immunoassay for point-of-care detection of cardiac biomarkers in acute myocardial infarction

人工智能驱动的侧向流动免疫分析法用于急性心肌梗死患者心脏生物标志物的即时检测

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Abstract

A functionalized gold nanoparticle-based lateral flow immunoassay (AuNPs-LFIA) platform integrated with a deep learning-based machine vision model for the rapid and quantitative detection of cardiac biomarkers, myoglobin (Myo) and cardiac troponin I (cTnI). AuNPs@Ab probes with high specificity and stability were prepared. AuNPs were synthesized via the citrate reduction method, functionalized with HS-PEG-COOH, and covalently conjugated to antibodies through EDC/NHS-mediated coupling to yield high specificity and stability. Using this platform, the machine vision-assisted AuNPs-LFIA achieved detection limits of 0.224 ng/mL for Myo and 0.071 ng/mL for cTnI. Quantitative readouts were obtained within 8 min, representing a 46.7% improvement in detection efficiency compared to conventional methods. Analysis of spiked serum samples demonstrated a significant correlation with commercial assay kits (R² > 0.99), further validating the platform’s accuracy and clinical applicability. Overall, this AI-enhanced AuNPs-LFIA platform offers sensitive, rapid, and user-friendly quantification. Its robust scalability provides a practical strategy for point-of-care testing (POCT) in cardiovascular diagnostics, particularly in resource-limited settings. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00604-026-08054-y.

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