Interpretating SPR-Derived Reaction Kinetics via Self-Organizing Maps for Diagnostic Applications.

ABSTRACT: Biosensors emerge as promising, cost-effective infectious disease diagnostics in resource-limited settings, requiring neither laboratory infrastructure nor specialized personnel. Surface plasmon resonance (SPR)-based biosensors remain preeminent for label-free, real-time analysis of biological interactions and kinetic parameter determination. Integrating Artificial Intelligence (AI), particularly self-organizing maps (SOMs), automates infection screening by projecting high-dimensional data onto topology-preserving 2D maps, offering advantages in diagnostic strategies by enabling efficient classification of infected vs healthy patients. This study presents an SPR biosensor with SOM analysis to enhance serodiagnosis of canine visceral leishmaniasis (CVL), a neglected tropical disease, whose

SUBMITTER: Volpe J 

PROVIDER: S-EPMC12560123 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature