AI Powered Platform: Microbiome-Driven Cardiovascular Diagnostics Via Smart Microneedle Patch Integration

Danya Sri Anantha Prakash, Jachin Thilak, Aashna Gupta, Diya Anne

Abstract: Cardiovascular disease is a leading global cause of mortality, yet traditional diagnostic tools often overlook the gut microbiome's role in disease progression. This study introduces an AI-powered microneedle patch that detects microbiome-related biomarkers, offering a noninvasive diagnostic approach for early-stage cardiovascular conditions. The patch, coated with specific antibodies, initiates redox reactions upon detecting microbial proteins, producing measurable signals for real-time analysis. Complemented by a machine learning-based web system trained on symptom-disease associations, the platform allows for dual-mode diagnostics using user-reported inputs and biosensor data. Designed with accessibility in mind, especially for underserved areas, this platform presents a novel convergence of artificial intelligence, biosensing, and microbiome science for personalized cardiovascular risk assessment. Despite growing evidence linking microbial bacterial, viral, and fungal infections to cardiovascular conditions, early diagnostic tools remain limited, particularly in underserved regions. To address this gap, we developed a noninvasive, AI-powered microneedle patch that detects microbiome-related biomarkers in blood. Coated with antibodies specific to disease-associated microbial proteins and metabolites, the patch initiates redox reactions to generate measurable signals for real-time analysis. Complementing the patch, we designed a machine learning-based online platform that leverages biosensor data and user-reported symptoms to provide rapid disease identification and cardiovascular risk assessment. Built using a neural network trained on synthetic symptom-disease mappings via TensorFlow/Keras, the model outputs the most likely diagnosis with a probability score. This dual-mode diagnostic platform, combining biosensing with artificial intelligence which offers a novel and accessible solution for personalized cardiovascular care, particularly benefiting under-resourced populations.

Keywords: Microbiome Diagnostics, Microneedle Patch, Cardiovascular Disease, Artificial Intelligence, Noninvasive Biosensors