The KRAS mutation is a crucial biomarker for determining targeted cancer therapies, making its accurate and cost-effective detection vital for precision oncology. However, current methodologies, such as next-generation sequencing (NGS) or PCR-based methods, are often expensive and technically complex, limiting their accessibility. Here, we present a novel bioassay for KRAS G12V mutation analysis that combines rolling circle amplification (RCA) with locked nucleic acid (LNA)-modified magnetic beads, electrochemical detection using carbon electrode chips, and AI-assisted analysis via a logistic regression classifier. Our platform demonstrated exceptional selectivity in distinguishing the KRAS G12V mutation from wild-type (wt) sequences, enabling analysis <
1 % of mutated DNA in a wt sample. We validated the bioassay on 7 cancer cell lines and 11 patient-derived samples, achieving results that perfectly correlated with NGS data. This innovative approach simplifies the workflow, reduces costs, and offers high sensitivity and specificity, making it a promising tool for clinical diagnostics and personalized cancer treatment strategies.